[SPARK-43225][BUILD][SQL] Remove jackson-core-asl and jackson-mapper-asl from pre-built distribution #40893
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wangyum
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It drops support for building w/ pre Hive 2.3.9, then SPARK-37446 can be reverted. |
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CC @srowen |
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Is this possible now that Hadoop 2 support is gone? just checking what the implications of this change are. |
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Yes, @sunchao I suppose Spark does not officially support building against Hive other than 2.3.9, for cases listed in SPARK-37446, it's the vendor's responsibility to port HIVE-21563 into their maintained Hive 2.3.8-[vender-custom-version] |
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@sunchao can we expect a new release(focus on security) for Hive 2.3? Considering Spark master and all maintained branches use Hive 2.3.9, which was reported some CVEs, from thrift, guava, log4j, jackson, etc. Or, Spark should move forward to a new Hive version. (should take much effort and not sure of benefits other than getting rid of CVEs) |
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@pan3793 AFAIK the development efforts in Hive community are only in Hive 3.x/4.x at the moment, and the 2.x branch is barely maintained. I can try to start a conversation in the Hive community to have a new 2.3.10 release and see how it looks like. From the long term perspective, it'd be better for Spark to move to Hive 3.x/4.x. |
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OK, am I right that this does not make Spark any less compatible with any version of Hive that is currently supported (>= 2.3.9)? If so then this is fine |
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Yes. |
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Merged to master |
srowen
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Apr 29, 2023
### What changes were proposed in this pull request? Call Hive 2.3.9 API directly instead of reflection, basically reverts SPARK-37446. ### Why are the changes needed? Switch to direct calling to achieve compile time check. Spark does not officially support building against Hive other than 2.3.9, for cases listed in SPARK-37446, it's the vendor's responsibility to port HIVE-21563 into their maintained Hive 2.3.8-[vender-custom-version]. See full discussion in #40893. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Pass GA. Closes #40995 from pan3793/SPARK-43320. Authored-by: Cheng Pan <[email protected]> Signed-off-by: Sean Owen <[email protected]>
LuciferYang
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May 10, 2023
### What changes were proposed in this pull request? Call Hive 2.3.9 API directly instead of reflection, basically reverts SPARK-37446. ### Why are the changes needed? Switch to direct calling to achieve compile time check. Spark does not officially support building against Hive other than 2.3.9, for cases listed in SPARK-37446, it's the vendor's responsibility to port HIVE-21563 into their maintained Hive 2.3.8-[vender-custom-version]. See full discussion in apache#40893. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Pass GA. Closes apache#40995 from pan3793/SPARK-43320. Authored-by: Cheng Pan <[email protected]> Signed-off-by: Sean Owen <[email protected]>
dongjoon-hyun
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Feb 21, 2024
### What changes were proposed in this pull request? This PR aims to provide a new profile, `hive-jackson-provided`, for Apache Spark 4.0.0. ### Why are the changes needed? Since Apache Hadoop 3.3.5, only Apache Hive requires old CodeHaus Jackson dependencies. Apache Spark 3.5.0 tried to eliminate them completely but it's reverted due to Hive UDF support. - #40893 - #42446 To allow Apache Spark 4.0 users - To provide their own CodeHaus Jackson libraries - To exclude them completely if they don't use `Hive UDF`. ### Does this PR introduce _any_ user-facing change? No, this is a new profile. ### How was this patch tested? Pass the CIs and manual build. **Without `hive-jackson-provided`** ``` $ dev/make-distribution.sh -Phive,hive-thriftserver $ ls -al dist/jars/*asl* -rw-r--r-- 1 dongjoon staff 232248 Feb 21 10:53 dist.org/jars/jackson-core-asl-1.9.13.jar -rw-r--r-- 1 dongjoon staff 780664 Feb 21 10:53 dist.org/jars/jackson-mapper-asl-1.9.13.jar ``` **With `hive-jackson-provided`** ``` $ dev/make-distribution.sh -Phive,hive-thriftserver,hive-jackson-provided $ ls -al dist/jars/*asl* zsh: no matches found: dist/jars/*asl* $ ls -al dist/jars/*hive* -rw-r--r-- 1 dongjoon staff 183633 Feb 21 11:00 dist/jars/hive-beeline-2.3.9.jar -rw-r--r-- 1 dongjoon staff 44704 Feb 21 11:00 dist/jars/hive-cli-2.3.9.jar -rw-r--r-- 1 dongjoon staff 436169 Feb 21 11:00 dist/jars/hive-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 10840949 Feb 21 11:00 dist/jars/hive-exec-2.3.9-core.jar -rw-r--r-- 1 dongjoon staff 116364 Feb 21 11:00 dist/jars/hive-jdbc-2.3.9.jar -rw-r--r-- 1 dongjoon staff 326585 Feb 21 11:00 dist/jars/hive-llap-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 8195966 Feb 21 11:00 dist/jars/hive-metastore-2.3.9.jar -rw-r--r-- 1 dongjoon staff 916630 Feb 21 11:00 dist/jars/hive-serde-2.3.9.jar -rw-r--r-- 1 dongjoon staff 1679366 Feb 21 11:00 dist/jars/hive-service-rpc-3.1.3.jar -rw-r--r-- 1 dongjoon staff 53902 Feb 21 11:00 dist/jars/hive-shims-0.23-2.3.9.jar -rw-r--r-- 1 dongjoon staff 8786 Feb 21 11:00 dist/jars/hive-shims-2.3.9.jar -rw-r--r-- 1 dongjoon staff 120293 Feb 21 11:00 dist/jars/hive-shims-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 12923 Feb 21 11:00 dist/jars/hive-shims-scheduler-2.3.9.jar -rw-r--r-- 1 dongjoon staff 258346 Feb 21 11:00 dist/jars/hive-storage-api-2.8.1.jar -rw-r--r-- 1 dongjoon staff 581739 Feb 21 11:00 dist/jars/spark-hive-thriftserver_2.13-4.0.0-SNAPSHOT.jar -rw-r--r-- 1 dongjoon staff 687446 Feb 21 11:00 dist/jars/spark-hive_2.13-4.0.0-SNAPSHOT.jar ``` ### Was this patch authored or co-authored using generative AI tooling? No. Closes #45201 from dongjoon-hyun/SPARK-47119. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
dongjoon-hyun
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Feb 24, 2024
… a new optional directory ### What changes were proposed in this pull request? This PR aims to provide `Apache Hive`'s `CodeHaus Jackson` dependencies via a new optional directory, `hive-jackson`, instead of the standard `jars` directory of Apache Spark binary distribution. Additionally, two internal configurations are added whose default values are `hive-jackson/*`. - `spark.driver.defaultExtraClassPath` - `spark.executor.defaultExtraClassPath` For example, Apache Spark distributions have been providing `spark-*-yarn-shuffle.jar` file under `yarn` directory instead of `jars`. **YARN SHUFFLE EXAMPLE** ``` $ ls -al yarn/*jar -rw-r--r-- 1 dongjoon staff 77352048 Sep 8 19:08 yarn/spark-3.5.0-yarn-shuffle.jar ``` This PR changes `Apache Hive`'s `CodeHaus Jackson` dependencies in a similar way. **BEFORE** ``` $ ls -al jars/*asl* -rw-r--r-- 1 dongjoon staff 232248 Sep 8 19:08 jars/jackson-core-asl-1.9.13.jar -rw-r--r-- 1 dongjoon staff 780664 Sep 8 19:08 jars/jackson-mapper-asl-1.9.13.jar ``` **AFTER** ``` $ ls -al jars/*asl* zsh: no matches found: jars/*asl* $ ls -al hive-jackson total 1984 drwxr-xr-x 4 dongjoon staff 128 Feb 23 15:37 . drwxr-xr-x 16 dongjoon staff 512 Feb 23 16:34 .. -rw-r--r-- 1 dongjoon staff 232248 Feb 23 15:37 jackson-core-asl-1.9.13.jar -rw-r--r-- 1 dongjoon staff 780664 Feb 23 15:37 jackson-mapper-asl-1.9.13.jar ``` ### Why are the changes needed? Since Apache Hadoop 3.3.5, only Apache Hive requires old CodeHaus Jackson dependencies. Apache Spark 3.5.0 tried to eliminate them completely but it's reverted due to Hive UDF support. - #40893 - #42446 SPARK-47119 added a way to exclude Apache Hive Jackson dependencies at the distribution building stage for Apache Spark 4.0.0. - #45201 This PR provides a way to exclude Apache Hive Jackson dependencies at runtime for Apache Spark 4.0.0. - Spark Shell without Apache Hive Jackson dependencies. ``` $ bin/spark-shell --driver-default-class-path "" ``` - Spark SQL Shell without Apache Hive Jackson dependencies. ``` $ bin/spark-sql --driver-default-class-path "" ``` - Spark Thrift Server without Apache Hive Jackson dependencies. ``` $ sbin/start-thriftserver.sh --driver-default-class-path "" ``` In addition, last but not least, this PR eliminates `CodeHaus Jackson` dependencies from the following Apache Spark deamons (using `spark-daemon.sh start`) because they don't require Hive `CodeHaus Jackson` dependencies - Spark Master - Spark Worker - Spark History Server ``` $ grep 'spark-daemon.sh start' * start-history-server.sh:exec "${SPARK_HOME}/sbin"/spark-daemon.sh start $CLASS 1 "$" start-master.sh:"${SPARK_HOME}/sbin"/spark-daemon.sh start $CLASS 1 \ start-worker.sh: "${SPARK_HOME}/sbin"/spark-daemon.sh start $CLASS $WORKER_NUM \ ``` ### Does this PR introduce _any_ user-facing change? No. There is no user-facing change by default. - For the distributions with `hive-jackson-provided` profile, the `scope` of Apache Hive Jackson dependencies is `provided` and `hive-jackson` directory is not created at all. - For the distributions with default setting, the `scope` of Apache Hive Jackson dependencies is still `compile`. In addition, they are in the Apache Spark's built-in class path like the following.  - The following Spark Deamon don't use `CodeHaus Jackson` dependencies. - Spark Master - Spark Worker - Spark History Server ### How was this patch tested? Pass the CIs and manually build a distribution and check the class paths in the `Environment` Tab. ``` $ dev/make-distribution.sh -Phive,hive-thriftserver ``` ### Was this patch authored or co-authored using generative AI tooling? No. Closes #45237 from dongjoon-hyun/SPARK-47152. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
ericm-db
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Mar 5, 2024
### What changes were proposed in this pull request? This PR aims to provide a new profile, `hive-jackson-provided`, for Apache Spark 4.0.0. ### Why are the changes needed? Since Apache Hadoop 3.3.5, only Apache Hive requires old CodeHaus Jackson dependencies. Apache Spark 3.5.0 tried to eliminate them completely but it's reverted due to Hive UDF support. - apache#40893 - apache#42446 To allow Apache Spark 4.0 users - To provide their own CodeHaus Jackson libraries - To exclude them completely if they don't use `Hive UDF`. ### Does this PR introduce _any_ user-facing change? No, this is a new profile. ### How was this patch tested? Pass the CIs and manual build. **Without `hive-jackson-provided`** ``` $ dev/make-distribution.sh -Phive,hive-thriftserver $ ls -al dist/jars/*asl* -rw-r--r-- 1 dongjoon staff 232248 Feb 21 10:53 dist.org/jars/jackson-core-asl-1.9.13.jar -rw-r--r-- 1 dongjoon staff 780664 Feb 21 10:53 dist.org/jars/jackson-mapper-asl-1.9.13.jar ``` **With `hive-jackson-provided`** ``` $ dev/make-distribution.sh -Phive,hive-thriftserver,hive-jackson-provided $ ls -al dist/jars/*asl* zsh: no matches found: dist/jars/*asl* $ ls -al dist/jars/*hive* -rw-r--r-- 1 dongjoon staff 183633 Feb 21 11:00 dist/jars/hive-beeline-2.3.9.jar -rw-r--r-- 1 dongjoon staff 44704 Feb 21 11:00 dist/jars/hive-cli-2.3.9.jar -rw-r--r-- 1 dongjoon staff 436169 Feb 21 11:00 dist/jars/hive-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 10840949 Feb 21 11:00 dist/jars/hive-exec-2.3.9-core.jar -rw-r--r-- 1 dongjoon staff 116364 Feb 21 11:00 dist/jars/hive-jdbc-2.3.9.jar -rw-r--r-- 1 dongjoon staff 326585 Feb 21 11:00 dist/jars/hive-llap-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 8195966 Feb 21 11:00 dist/jars/hive-metastore-2.3.9.jar -rw-r--r-- 1 dongjoon staff 916630 Feb 21 11:00 dist/jars/hive-serde-2.3.9.jar -rw-r--r-- 1 dongjoon staff 1679366 Feb 21 11:00 dist/jars/hive-service-rpc-3.1.3.jar -rw-r--r-- 1 dongjoon staff 53902 Feb 21 11:00 dist/jars/hive-shims-0.23-2.3.9.jar -rw-r--r-- 1 dongjoon staff 8786 Feb 21 11:00 dist/jars/hive-shims-2.3.9.jar -rw-r--r-- 1 dongjoon staff 120293 Feb 21 11:00 dist/jars/hive-shims-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 12923 Feb 21 11:00 dist/jars/hive-shims-scheduler-2.3.9.jar -rw-r--r-- 1 dongjoon staff 258346 Feb 21 11:00 dist/jars/hive-storage-api-2.8.1.jar -rw-r--r-- 1 dongjoon staff 581739 Feb 21 11:00 dist/jars/spark-hive-thriftserver_2.13-4.0.0-SNAPSHOT.jar -rw-r--r-- 1 dongjoon staff 687446 Feb 21 11:00 dist/jars/spark-hive_2.13-4.0.0-SNAPSHOT.jar ``` ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#45201 from dongjoon-hyun/SPARK-47119. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
ericm-db
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Mar 5, 2024
… a new optional directory ### What changes were proposed in this pull request? This PR aims to provide `Apache Hive`'s `CodeHaus Jackson` dependencies via a new optional directory, `hive-jackson`, instead of the standard `jars` directory of Apache Spark binary distribution. Additionally, two internal configurations are added whose default values are `hive-jackson/*`. - `spark.driver.defaultExtraClassPath` - `spark.executor.defaultExtraClassPath` For example, Apache Spark distributions have been providing `spark-*-yarn-shuffle.jar` file under `yarn` directory instead of `jars`. **YARN SHUFFLE EXAMPLE** ``` $ ls -al yarn/*jar -rw-r--r-- 1 dongjoon staff 77352048 Sep 8 19:08 yarn/spark-3.5.0-yarn-shuffle.jar ``` This PR changes `Apache Hive`'s `CodeHaus Jackson` dependencies in a similar way. **BEFORE** ``` $ ls -al jars/*asl* -rw-r--r-- 1 dongjoon staff 232248 Sep 8 19:08 jars/jackson-core-asl-1.9.13.jar -rw-r--r-- 1 dongjoon staff 780664 Sep 8 19:08 jars/jackson-mapper-asl-1.9.13.jar ``` **AFTER** ``` $ ls -al jars/*asl* zsh: no matches found: jars/*asl* $ ls -al hive-jackson total 1984 drwxr-xr-x 4 dongjoon staff 128 Feb 23 15:37 . drwxr-xr-x 16 dongjoon staff 512 Feb 23 16:34 .. -rw-r--r-- 1 dongjoon staff 232248 Feb 23 15:37 jackson-core-asl-1.9.13.jar -rw-r--r-- 1 dongjoon staff 780664 Feb 23 15:37 jackson-mapper-asl-1.9.13.jar ``` ### Why are the changes needed? Since Apache Hadoop 3.3.5, only Apache Hive requires old CodeHaus Jackson dependencies. Apache Spark 3.5.0 tried to eliminate them completely but it's reverted due to Hive UDF support. - apache#40893 - apache#42446 SPARK-47119 added a way to exclude Apache Hive Jackson dependencies at the distribution building stage for Apache Spark 4.0.0. - apache#45201 This PR provides a way to exclude Apache Hive Jackson dependencies at runtime for Apache Spark 4.0.0. - Spark Shell without Apache Hive Jackson dependencies. ``` $ bin/spark-shell --driver-default-class-path "" ``` - Spark SQL Shell without Apache Hive Jackson dependencies. ``` $ bin/spark-sql --driver-default-class-path "" ``` - Spark Thrift Server without Apache Hive Jackson dependencies. ``` $ sbin/start-thriftserver.sh --driver-default-class-path "" ``` In addition, last but not least, this PR eliminates `CodeHaus Jackson` dependencies from the following Apache Spark deamons (using `spark-daemon.sh start`) because they don't require Hive `CodeHaus Jackson` dependencies - Spark Master - Spark Worker - Spark History Server ``` $ grep 'spark-daemon.sh start' * start-history-server.sh:exec "${SPARK_HOME}/sbin"/spark-daemon.sh start $CLASS 1 "$" start-master.sh:"${SPARK_HOME}/sbin"/spark-daemon.sh start $CLASS 1 \ start-worker.sh: "${SPARK_HOME}/sbin"/spark-daemon.sh start $CLASS $WORKER_NUM \ ``` ### Does this PR introduce _any_ user-facing change? No. There is no user-facing change by default. - For the distributions with `hive-jackson-provided` profile, the `scope` of Apache Hive Jackson dependencies is `provided` and `hive-jackson` directory is not created at all. - For the distributions with default setting, the `scope` of Apache Hive Jackson dependencies is still `compile`. In addition, they are in the Apache Spark's built-in class path like the following.  - The following Spark Deamon don't use `CodeHaus Jackson` dependencies. - Spark Master - Spark Worker - Spark History Server ### How was this patch tested? Pass the CIs and manually build a distribution and check the class paths in the `Environment` Tab. ``` $ dev/make-distribution.sh -Phive,hive-thriftserver ``` ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#45237 from dongjoon-hyun/SPARK-47152. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
prabhjyotsingh
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Apr 9, 2024
…asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7)
prabhjyotsingh
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Apr 9, 2024
…asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action ### What changes were proposed in this pull request? This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. ### Why are the changes needed? After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions:
prabhjyotsingh
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Apr 9, 2024
…asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions:
prabhjyotsingh
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Apr 9, 2024
…n-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions:
prabhjyotsingh
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May 2, 2024
…n-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28)
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May 2, 2024
…n-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml
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* ODP-1304 [SPARK-44914][BUILD] Upgrade Apache Ivy to 2.5.2 This PR aims to upgrade Apache Ivy to 2.5.2 and protect old Ivy-based systems like old Spark from Apache Ivy 2.5.2's incompatibility by introducing a new `.ivy2.5.2` directory. - Apache Spark 4.0.0 will create this once and reuse this directory while all the other systems like old Sparks uses the old one, `.ivy2`. So, the behavior is the same with the case where Apache Spark 4.0.0 is installed and used in a new machine. - For the environments with `User-provided Ivy-path`es, the user might hit the incompatibility still. However, the users can mitigate them because they already have full control on `Ivy-path`es. This was tried once and reverted logically due to Java 11 and Java 17 failures in Daily CIs. - apache#42613 - apache#42668 Currently, PR Builder also fails as of now. If the PR passes CIes, we can achieve the following. - [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) - FIX: CVE-2022-46751: Apache Ivy Is Vulnerable to XML External Entity Injections No. Pass the CIs including `HiveExternalCatalogVersionsSuite`. No. Closes apache#45075 from dongjoon-hyun/SPARK-44914. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 3baa60a) [SPARK-44968][BUILD] Downgrade ivy from 2.5.2 to 2.5.1 ### What changes were proposed in this pull request? After upgrading Ivy from 2.5.1 to 2.5.2 in SPARK-44914, daily tests for Java 11 and Java 17 began to experience ABORTED in the `HiveExternalCatalogVersionsSuite` test. Java 11 - https://github.com/apache/spark/actions/runs/5953716283/job/16148657660 - https://github.com/apache/spark/actions/runs/5966131923/job/16185159550 Java 17 - https://github.com/apache/spark/actions/runs/5956925790/job/16158714165 - https://github.com/apache/spark/actions/runs/5969348559/job/16195073478 ``` 2023-08-23T23:00:49.6547573Z [info] 2023-08-23 16:00:48.209 - stdout> : java.lang.RuntimeException: problem during retrieve of org.apache.spark#spark-submit-parent-4c061f04-b951-4d06-8909-cde5452988d9: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6548745Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:238) 2023-08-23T23:00:49.6549572Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:89) 2023-08-23T23:00:49.6550334Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.Ivy.retrieve(Ivy.java:551) 2023-08-23T23:00:49.6551079Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.deploy.SparkSubmitUtils$.resolveMavenCoordinates(SparkSubmit.scala:1464) 2023-08-23T23:00:49.6552024Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.$anonfun$downloadVersion$2(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6552884Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.util.package$.quietly(package.scala:42) 2023-08-23T23:00:49.6553755Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.downloadVersion(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6554705Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.liftedTree1$1(IsolatedClientLoader.scala:65) 2023-08-23T23:00:49.6555637Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.forVersion(IsolatedClientLoader.scala:64) 2023-08-23T23:00:49.6556554Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:443) 2023-08-23T23:00:49.6557340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:356) 2023-08-23T23:00:49.6558187Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client$lzycompute(HiveExternalCatalog.scala:71) 2023-08-23T23:00:49.6559061Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client(HiveExternalCatalog.scala:70) 2023-08-23T23:00:49.6559962Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$databaseExists$1(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6560766Z [info] 2023-08-23 16:00:48.209 - stdout> at scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23) 2023-08-23T23:00:49.6561584Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:102) 2023-08-23T23:00:49.6562510Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6563435Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:150) 2023-08-23T23:00:49.6564323Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:140) 2023-08-23T23:00:49.6565340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:45) 2023-08-23T23:00:49.6566321Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.$anonfun$catalog$1(HiveSessionStateBuilder.scala:60) 2023-08-23T23:00:49.6567363Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog$lzycompute(SessionCatalog.scala:118) 2023-08-23T23:00:49.6568372Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog(SessionCatalog.scala:118) 2023-08-23T23:00:49.6569393Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.tableExists(SessionCatalog.scala:490) 2023-08-23T23:00:49.6570685Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.CreateDataSourceTableAsSelectCommand.run(createDataSourceTables.scala:155) 2023-08-23T23:00:49.6571842Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113) 2023-08-23T23:00:49.6572932Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111) 2023-08-23T23:00:49.6573996Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125) 2023-08-23T23:00:49.6575045Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:97) 2023-08-23T23:00:49.6576066Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) 2023-08-23T23:00:49.6576937Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) 2023-08-23T23:00:49.6577807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) 2023-08-23T23:00:49.6578620Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6579432Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) 2023-08-23T23:00:49.6580357Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:97) 2023-08-23T23:00:49.6581331Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:93) 2023-08-23T23:00:49.6582239Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:481) 2023-08-23T23:00:49.6583101Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82) 2023-08-23T23:00:49.6584088Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:481) 2023-08-23T23:00:49.6585236Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6586519Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) 2023-08-23T23:00:49.6587686Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) 2023-08-23T23:00:49.6588898Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590014Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590993Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:457) 2023-08-23T23:00:49.6591930Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:93) 2023-08-23T23:00:49.6592914Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:80) 2023-08-23T23:00:49.6593856Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:78) 2023-08-23T23:00:49.6594687Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:219) 2023-08-23T23:00:49.6595379Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99) 2023-08-23T23:00:49.6596103Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6596807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:96) 2023-08-23T23:00:49.6597520Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:618) 2023-08-23T23:00:49.6598276Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6599022Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:613) 2023-08-23T23:00:49.6599819Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 2023-08-23T23:00:49.6600723Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77) 2023-08-23T23:00:49.6601707Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 2023-08-23T23:00:49.6602513Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.reflect.Method.invoke(Method.java:568) 2023-08-23T23:00:49.6603272Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) 2023-08-23T23:00:49.6604007Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) 2023-08-23T23:00:49.6604724Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.Gateway.invoke(Gateway.java:282) 2023-08-23T23:00:49.6605416Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) 2023-08-23T23:00:49.6606209Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.CallCommand.execute(CallCommand.java:79) 2023-08-23T23:00:49.6606969Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) 2023-08-23T23:00:49.6607743Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.run(ClientServerConnection.java:106) 2023-08-23T23:00:49.6608415Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.Thread.run(Thread.java:833) 2023-08-23T23:00:49.6609288Z [info] 2023-08-23 16:00:48.209 - stdout> Caused by: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6610288Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.determineArtifactsToCopy(RetrieveEngine.java:426) 2023-08-23T23:00:49.6611332Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:122) 2023-08-23T23:00:49.6612046Z [info] 2023-08-23 16:00:48.209 - stdout> ... 66 more 2023-08-23T23:00:49.6612498Z [info] 2023-08-23 16:00:48.209 - stdout> ``` So this pr downgrade ivy from 2.5.2 to 2.5.1 to restore Java 11/17 daily tests. ### Why are the changes needed? To restore Java 11/17 daily tests. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By changing the default Java version in `build_and_test.yml` to 17 for verification, the tests succeed after downgrading the Ivy to 2.5.1. - https://github.com/LuciferYang/spark/actions/runs/5972232677/job/16209970934 <img width="1116" alt="image" src="https://github.com/apache/spark/assets/1475305/cd4002d8-893d-4845-8b2e-c01ff3106f7f"> ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#42668 from LuciferYang/test-java17. Authored-by: yangjie01 <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 4f8a199) [SPARK-44914][BUILD] Upgrade `Apache ivy` from 2.5.1 to 2.5.2 Upgrade Apache ivy from 2.5.1 to 2.5.2 [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) [CVE-2022-46751](https://www.cve.org/CVERecord?id=CVE-2022-46751) The fix apache/ant-ivy@2be17bc No. Pass GA No. Closes apache#42613 from bjornjorgensen/ivy-2.5.2. Authored-by: Bjørn Jørgensen <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 611e17e) [SPARK-41030][BUILD] Upgrade `Apache Ivy` to 2.5.1 Upgrade `Apache Ivy` from 2.5.0 to 2.5.1 [Release notes](https://ant.apache.org/ivy/history/2.5.1/release-notes.html) [CVE-2022-37865](https://www.cve.org/CVERecord?id=CVE-2022-37865) and [CVE-2022-37866](https://nvd.nist.gov/vuln/detail/CVE-2022-37866) No. Pass GA Closes apache#38539 from bjornjorgensen/ivy-2.5.1. Authored-by: Bjørn <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 4bbdca6) (cherry picked from commit 0e5fa79) # Conflicts: # dev/deps/spark-deps-hadoop-2-hive-2.3 # dev/deps/spark-deps-hadoop-3-hive-2.3 # docs/core-migration-guide.md # pom.xml * ODP-1303 [SPARK-45732][BUILD] Upgrade commons-text to 1.11.0 The pr aims to upgrade `commons-text` from `1.10.0` to `1.11.0`. Release note: https://commons.apache.org/proper/commons-text/changes-report.html#a1.11.0 includes some bug fix, eg: - Fix StringTokenizer.getTokenList to return an independent modifiable list. Fixes [TEXT-219](https://issues.apache.org/jira/browse/TEXT-219). - Fix TextStringBuilder to over-allocate when ensuring capacity apache#452. Fixes [TEXT-228](https://issues.apache.org/jira/browse/TEXT-228). - TextStringBuidler#hashCode() allocates a String on each call apache#387. No. Pass GA. No. Closes apache#43590 from panbingkun/SPARK-45732. Authored-by: panbingkun <[email protected]> Signed-off-by: Hyukjin Kwon <[email protected]> (cherry picked from commit d38f074) [SPARK-40801][BUILD] Upgrade `Apache commons-text` to 1.10 Upgrade Apache commons-text from 1.9 to 1.10.0 [CVE-2022-42889](https://nvd.nist.gov/vuln/detail/CVE-2022-42889) No. Pass github action Closes apache#38262 from bjornjorgensen/commons-text-1.10. Authored-by: Bjørn <[email protected]> Signed-off-by: Yuming Wang <[email protected]> (cherry picked from commit 99abc94) [SPARK-38231][BUILD] Upgrade commons-text to 1.9 This PR aims to upgrade commons-text to 1.9. 1.9 is the latest and popular than 1.6. - https://commons.apache.org/proper/commons-text/changes-report.html#a1.9 - https://mvnrepository.com/artifact/org.apache.commons/commons-text No Pass GA Closes apache#35542 from LuciferYang/upgrade-common-text. Authored-by: yangjie01 <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 70f5bfd) (cherry picked from commit 5cb61e7) # Conflicts: # pom.xml * ODP-1302 [SPARK-43225][BUILD][SQL] Remove jackson-core-asl and jackson-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml --------- Co-authored-by: Dongjoon Hyun <[email protected]> Co-authored-by: Yuming Wang <[email protected]>
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Jun 28, 2024
* ODP-1304 [SPARK-44914][BUILD] Upgrade Apache Ivy to 2.5.2 This PR aims to upgrade Apache Ivy to 2.5.2 and protect old Ivy-based systems like old Spark from Apache Ivy 2.5.2's incompatibility by introducing a new `.ivy2.5.2` directory. - Apache Spark 4.0.0 will create this once and reuse this directory while all the other systems like old Sparks uses the old one, `.ivy2`. So, the behavior is the same with the case where Apache Spark 4.0.0 is installed and used in a new machine. - For the environments with `User-provided Ivy-path`es, the user might hit the incompatibility still. However, the users can mitigate them because they already have full control on `Ivy-path`es. This was tried once and reverted logically due to Java 11 and Java 17 failures in Daily CIs. - apache#42613 - apache#42668 Currently, PR Builder also fails as of now. If the PR passes CIes, we can achieve the following. - [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) - FIX: CVE-2022-46751: Apache Ivy Is Vulnerable to XML External Entity Injections No. Pass the CIs including `HiveExternalCatalogVersionsSuite`. No. Closes apache#45075 from dongjoon-hyun/SPARK-44914. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 3baa60a) [SPARK-44968][BUILD] Downgrade ivy from 2.5.2 to 2.5.1 ### What changes were proposed in this pull request? After upgrading Ivy from 2.5.1 to 2.5.2 in SPARK-44914, daily tests for Java 11 and Java 17 began to experience ABORTED in the `HiveExternalCatalogVersionsSuite` test. Java 11 - https://github.com/apache/spark/actions/runs/5953716283/job/16148657660 - https://github.com/apache/spark/actions/runs/5966131923/job/16185159550 Java 17 - https://github.com/apache/spark/actions/runs/5956925790/job/16158714165 - https://github.com/apache/spark/actions/runs/5969348559/job/16195073478 ``` 2023-08-23T23:00:49.6547573Z [info] 2023-08-23 16:00:48.209 - stdout> : java.lang.RuntimeException: problem during retrieve of org.apache.spark#spark-submit-parent-4c061f04-b951-4d06-8909-cde5452988d9: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6548745Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:238) 2023-08-23T23:00:49.6549572Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:89) 2023-08-23T23:00:49.6550334Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.Ivy.retrieve(Ivy.java:551) 2023-08-23T23:00:49.6551079Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.deploy.SparkSubmitUtils$.resolveMavenCoordinates(SparkSubmit.scala:1464) 2023-08-23T23:00:49.6552024Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.$anonfun$downloadVersion$2(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6552884Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.util.package$.quietly(package.scala:42) 2023-08-23T23:00:49.6553755Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.downloadVersion(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6554705Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.liftedTree1$1(IsolatedClientLoader.scala:65) 2023-08-23T23:00:49.6555637Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.forVersion(IsolatedClientLoader.scala:64) 2023-08-23T23:00:49.6556554Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:443) 2023-08-23T23:00:49.6557340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:356) 2023-08-23T23:00:49.6558187Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client$lzycompute(HiveExternalCatalog.scala:71) 2023-08-23T23:00:49.6559061Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client(HiveExternalCatalog.scala:70) 2023-08-23T23:00:49.6559962Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$databaseExists$1(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6560766Z [info] 2023-08-23 16:00:48.209 - stdout> at scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23) 2023-08-23T23:00:49.6561584Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:102) 2023-08-23T23:00:49.6562510Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6563435Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:150) 2023-08-23T23:00:49.6564323Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:140) 2023-08-23T23:00:49.6565340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:45) 2023-08-23T23:00:49.6566321Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.$anonfun$catalog$1(HiveSessionStateBuilder.scala:60) 2023-08-23T23:00:49.6567363Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog$lzycompute(SessionCatalog.scala:118) 2023-08-23T23:00:49.6568372Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog(SessionCatalog.scala:118) 2023-08-23T23:00:49.6569393Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.tableExists(SessionCatalog.scala:490) 2023-08-23T23:00:49.6570685Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.CreateDataSourceTableAsSelectCommand.run(createDataSourceTables.scala:155) 2023-08-23T23:00:49.6571842Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113) 2023-08-23T23:00:49.6572932Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111) 2023-08-23T23:00:49.6573996Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125) 2023-08-23T23:00:49.6575045Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:97) 2023-08-23T23:00:49.6576066Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) 2023-08-23T23:00:49.6576937Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) 2023-08-23T23:00:49.6577807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) 2023-08-23T23:00:49.6578620Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6579432Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) 2023-08-23T23:00:49.6580357Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:97) 2023-08-23T23:00:49.6581331Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:93) 2023-08-23T23:00:49.6582239Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:481) 2023-08-23T23:00:49.6583101Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82) 2023-08-23T23:00:49.6584088Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:481) 2023-08-23T23:00:49.6585236Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6586519Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) 2023-08-23T23:00:49.6587686Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) 2023-08-23T23:00:49.6588898Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590014Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590993Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:457) 2023-08-23T23:00:49.6591930Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:93) 2023-08-23T23:00:49.6592914Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:80) 2023-08-23T23:00:49.6593856Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:78) 2023-08-23T23:00:49.6594687Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:219) 2023-08-23T23:00:49.6595379Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99) 2023-08-23T23:00:49.6596103Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6596807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:96) 2023-08-23T23:00:49.6597520Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:618) 2023-08-23T23:00:49.6598276Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6599022Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:613) 2023-08-23T23:00:49.6599819Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 2023-08-23T23:00:49.6600723Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77) 2023-08-23T23:00:49.6601707Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 2023-08-23T23:00:49.6602513Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.reflect.Method.invoke(Method.java:568) 2023-08-23T23:00:49.6603272Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) 2023-08-23T23:00:49.6604007Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) 2023-08-23T23:00:49.6604724Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.Gateway.invoke(Gateway.java:282) 2023-08-23T23:00:49.6605416Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) 2023-08-23T23:00:49.6606209Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.CallCommand.execute(CallCommand.java:79) 2023-08-23T23:00:49.6606969Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) 2023-08-23T23:00:49.6607743Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.run(ClientServerConnection.java:106) 2023-08-23T23:00:49.6608415Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.Thread.run(Thread.java:833) 2023-08-23T23:00:49.6609288Z [info] 2023-08-23 16:00:48.209 - stdout> Caused by: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6610288Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.determineArtifactsToCopy(RetrieveEngine.java:426) 2023-08-23T23:00:49.6611332Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:122) 2023-08-23T23:00:49.6612046Z [info] 2023-08-23 16:00:48.209 - stdout> ... 66 more 2023-08-23T23:00:49.6612498Z [info] 2023-08-23 16:00:48.209 - stdout> ``` So this pr downgrade ivy from 2.5.2 to 2.5.1 to restore Java 11/17 daily tests. ### Why are the changes needed? To restore Java 11/17 daily tests. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By changing the default Java version in `build_and_test.yml` to 17 for verification, the tests succeed after downgrading the Ivy to 2.5.1. - https://github.com/LuciferYang/spark/actions/runs/5972232677/job/16209970934 <img width="1116" alt="image" src="https://github.com/apache/spark/assets/1475305/cd4002d8-893d-4845-8b2e-c01ff3106f7f"> ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#42668 from LuciferYang/test-java17. Authored-by: yangjie01 <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 4f8a199) [SPARK-44914][BUILD] Upgrade `Apache ivy` from 2.5.1 to 2.5.2 Upgrade Apache ivy from 2.5.1 to 2.5.2 [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) [CVE-2022-46751](https://www.cve.org/CVERecord?id=CVE-2022-46751) The fix apache/ant-ivy@2be17bc No. Pass GA No. Closes apache#42613 from bjornjorgensen/ivy-2.5.2. Authored-by: Bjørn Jørgensen <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 611e17e) [SPARK-41030][BUILD] Upgrade `Apache Ivy` to 2.5.1 Upgrade `Apache Ivy` from 2.5.0 to 2.5.1 [Release notes](https://ant.apache.org/ivy/history/2.5.1/release-notes.html) [CVE-2022-37865](https://www.cve.org/CVERecord?id=CVE-2022-37865) and [CVE-2022-37866](https://nvd.nist.gov/vuln/detail/CVE-2022-37866) No. Pass GA Closes apache#38539 from bjornjorgensen/ivy-2.5.1. Authored-by: Bjørn <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 4bbdca6) (cherry picked from commit 0e5fa79) # Conflicts: # dev/deps/spark-deps-hadoop-2-hive-2.3 # dev/deps/spark-deps-hadoop-3-hive-2.3 # docs/core-migration-guide.md # pom.xml * ODP-1303 [SPARK-45732][BUILD] Upgrade commons-text to 1.11.0 The pr aims to upgrade `commons-text` from `1.10.0` to `1.11.0`. Release note: https://commons.apache.org/proper/commons-text/changes-report.html#a1.11.0 includes some bug fix, eg: - Fix StringTokenizer.getTokenList to return an independent modifiable list. Fixes [TEXT-219](https://issues.apache.org/jira/browse/TEXT-219). - Fix TextStringBuilder to over-allocate when ensuring capacity apache#452. Fixes [TEXT-228](https://issues.apache.org/jira/browse/TEXT-228). - TextStringBuidler#hashCode() allocates a String on each call apache#387. No. Pass GA. No. Closes apache#43590 from panbingkun/SPARK-45732. Authored-by: panbingkun <[email protected]> Signed-off-by: Hyukjin Kwon <[email protected]> (cherry picked from commit d38f074) [SPARK-40801][BUILD] Upgrade `Apache commons-text` to 1.10 Upgrade Apache commons-text from 1.9 to 1.10.0 [CVE-2022-42889](https://nvd.nist.gov/vuln/detail/CVE-2022-42889) No. Pass github action Closes apache#38262 from bjornjorgensen/commons-text-1.10. Authored-by: Bjørn <[email protected]> Signed-off-by: Yuming Wang <[email protected]> (cherry picked from commit 99abc94) [SPARK-38231][BUILD] Upgrade commons-text to 1.9 This PR aims to upgrade commons-text to 1.9. 1.9 is the latest and popular than 1.6. - https://commons.apache.org/proper/commons-text/changes-report.html#a1.9 - https://mvnrepository.com/artifact/org.apache.commons/commons-text No Pass GA Closes apache#35542 from LuciferYang/upgrade-common-text. Authored-by: yangjie01 <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 70f5bfd) (cherry picked from commit 5cb61e7) # Conflicts: # pom.xml * ODP-1302 [SPARK-43225][BUILD][SQL] Remove jackson-core-asl and jackson-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml --------- Co-authored-by: Dongjoon Hyun <[email protected]> Co-authored-by: Yuming Wang <[email protected]>
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* ODP-1304 [SPARK-44914][BUILD] Upgrade Apache Ivy to 2.5.2 This PR aims to upgrade Apache Ivy to 2.5.2 and protect old Ivy-based systems like old Spark from Apache Ivy 2.5.2's incompatibility by introducing a new `.ivy2.5.2` directory. - Apache Spark 4.0.0 will create this once and reuse this directory while all the other systems like old Sparks uses the old one, `.ivy2`. So, the behavior is the same with the case where Apache Spark 4.0.0 is installed and used in a new machine. - For the environments with `User-provided Ivy-path`es, the user might hit the incompatibility still. However, the users can mitigate them because they already have full control on `Ivy-path`es. This was tried once and reverted logically due to Java 11 and Java 17 failures in Daily CIs. - apache#42613 - apache#42668 Currently, PR Builder also fails as of now. If the PR passes CIes, we can achieve the following. - [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) - FIX: CVE-2022-46751: Apache Ivy Is Vulnerable to XML External Entity Injections No. Pass the CIs including `HiveExternalCatalogVersionsSuite`. No. Closes apache#45075 from dongjoon-hyun/SPARK-44914. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 3baa60a) [SPARK-44968][BUILD] Downgrade ivy from 2.5.2 to 2.5.1 ### What changes were proposed in this pull request? After upgrading Ivy from 2.5.1 to 2.5.2 in SPARK-44914, daily tests for Java 11 and Java 17 began to experience ABORTED in the `HiveExternalCatalogVersionsSuite` test. Java 11 - https://github.com/apache/spark/actions/runs/5953716283/job/16148657660 - https://github.com/apache/spark/actions/runs/5966131923/job/16185159550 Java 17 - https://github.com/apache/spark/actions/runs/5956925790/job/16158714165 - https://github.com/apache/spark/actions/runs/5969348559/job/16195073478 ``` 2023-08-23T23:00:49.6547573Z [info] 2023-08-23 16:00:48.209 - stdout> : java.lang.RuntimeException: problem during retrieve of org.apache.spark#spark-submit-parent-4c061f04-b951-4d06-8909-cde5452988d9: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6548745Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:238) 2023-08-23T23:00:49.6549572Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:89) 2023-08-23T23:00:49.6550334Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.Ivy.retrieve(Ivy.java:551) 2023-08-23T23:00:49.6551079Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.deploy.SparkSubmitUtils$.resolveMavenCoordinates(SparkSubmit.scala:1464) 2023-08-23T23:00:49.6552024Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.$anonfun$downloadVersion$2(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6552884Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.util.package$.quietly(package.scala:42) 2023-08-23T23:00:49.6553755Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.downloadVersion(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6554705Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.liftedTree1$1(IsolatedClientLoader.scala:65) 2023-08-23T23:00:49.6555637Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.forVersion(IsolatedClientLoader.scala:64) 2023-08-23T23:00:49.6556554Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:443) 2023-08-23T23:00:49.6557340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:356) 2023-08-23T23:00:49.6558187Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client$lzycompute(HiveExternalCatalog.scala:71) 2023-08-23T23:00:49.6559061Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client(HiveExternalCatalog.scala:70) 2023-08-23T23:00:49.6559962Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$databaseExists$1(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6560766Z [info] 2023-08-23 16:00:48.209 - stdout> at scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23) 2023-08-23T23:00:49.6561584Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:102) 2023-08-23T23:00:49.6562510Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6563435Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:150) 2023-08-23T23:00:49.6564323Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:140) 2023-08-23T23:00:49.6565340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:45) 2023-08-23T23:00:49.6566321Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.$anonfun$catalog$1(HiveSessionStateBuilder.scala:60) 2023-08-23T23:00:49.6567363Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog$lzycompute(SessionCatalog.scala:118) 2023-08-23T23:00:49.6568372Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog(SessionCatalog.scala:118) 2023-08-23T23:00:49.6569393Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.tableExists(SessionCatalog.scala:490) 2023-08-23T23:00:49.6570685Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.CreateDataSourceTableAsSelectCommand.run(createDataSourceTables.scala:155) 2023-08-23T23:00:49.6571842Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113) 2023-08-23T23:00:49.6572932Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111) 2023-08-23T23:00:49.6573996Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125) 2023-08-23T23:00:49.6575045Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:97) 2023-08-23T23:00:49.6576066Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) 2023-08-23T23:00:49.6576937Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) 2023-08-23T23:00:49.6577807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) 2023-08-23T23:00:49.6578620Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6579432Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) 2023-08-23T23:00:49.6580357Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:97) 2023-08-23T23:00:49.6581331Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:93) 2023-08-23T23:00:49.6582239Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:481) 2023-08-23T23:00:49.6583101Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82) 2023-08-23T23:00:49.6584088Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:481) 2023-08-23T23:00:49.6585236Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6586519Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) 2023-08-23T23:00:49.6587686Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) 2023-08-23T23:00:49.6588898Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590014Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590993Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:457) 2023-08-23T23:00:49.6591930Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:93) 2023-08-23T23:00:49.6592914Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:80) 2023-08-23T23:00:49.6593856Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:78) 2023-08-23T23:00:49.6594687Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:219) 2023-08-23T23:00:49.6595379Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99) 2023-08-23T23:00:49.6596103Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6596807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:96) 2023-08-23T23:00:49.6597520Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:618) 2023-08-23T23:00:49.6598276Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6599022Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:613) 2023-08-23T23:00:49.6599819Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 2023-08-23T23:00:49.6600723Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77) 2023-08-23T23:00:49.6601707Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 2023-08-23T23:00:49.6602513Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.reflect.Method.invoke(Method.java:568) 2023-08-23T23:00:49.6603272Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) 2023-08-23T23:00:49.6604007Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) 2023-08-23T23:00:49.6604724Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.Gateway.invoke(Gateway.java:282) 2023-08-23T23:00:49.6605416Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) 2023-08-23T23:00:49.6606209Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.CallCommand.execute(CallCommand.java:79) 2023-08-23T23:00:49.6606969Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) 2023-08-23T23:00:49.6607743Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.run(ClientServerConnection.java:106) 2023-08-23T23:00:49.6608415Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.Thread.run(Thread.java:833) 2023-08-23T23:00:49.6609288Z [info] 2023-08-23 16:00:48.209 - stdout> Caused by: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6610288Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.determineArtifactsToCopy(RetrieveEngine.java:426) 2023-08-23T23:00:49.6611332Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:122) 2023-08-23T23:00:49.6612046Z [info] 2023-08-23 16:00:48.209 - stdout> ... 66 more 2023-08-23T23:00:49.6612498Z [info] 2023-08-23 16:00:48.209 - stdout> ``` So this pr downgrade ivy from 2.5.2 to 2.5.1 to restore Java 11/17 daily tests. ### Why are the changes needed? To restore Java 11/17 daily tests. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By changing the default Java version in `build_and_test.yml` to 17 for verification, the tests succeed after downgrading the Ivy to 2.5.1. - https://github.com/LuciferYang/spark/actions/runs/5972232677/job/16209970934 <img width="1116" alt="image" src="https://github.com/apache/spark/assets/1475305/cd4002d8-893d-4845-8b2e-c01ff3106f7f"> ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#42668 from LuciferYang/test-java17. Authored-by: yangjie01 <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 4f8a199) [SPARK-44914][BUILD] Upgrade `Apache ivy` from 2.5.1 to 2.5.2 Upgrade Apache ivy from 2.5.1 to 2.5.2 [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) [CVE-2022-46751](https://www.cve.org/CVERecord?id=CVE-2022-46751) The fix apache/ant-ivy@2be17bc No. Pass GA No. Closes apache#42613 from bjornjorgensen/ivy-2.5.2. Authored-by: Bjørn Jørgensen <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 611e17e) [SPARK-41030][BUILD] Upgrade `Apache Ivy` to 2.5.1 Upgrade `Apache Ivy` from 2.5.0 to 2.5.1 [Release notes](https://ant.apache.org/ivy/history/2.5.1/release-notes.html) [CVE-2022-37865](https://www.cve.org/CVERecord?id=CVE-2022-37865) and [CVE-2022-37866](https://nvd.nist.gov/vuln/detail/CVE-2022-37866) No. Pass GA Closes apache#38539 from bjornjorgensen/ivy-2.5.1. Authored-by: Bjørn <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 4bbdca6) (cherry picked from commit 0e5fa79) # Conflicts: # dev/deps/spark-deps-hadoop-2-hive-2.3 # dev/deps/spark-deps-hadoop-3-hive-2.3 # docs/core-migration-guide.md # pom.xml * ODP-1303 [SPARK-45732][BUILD] Upgrade commons-text to 1.11.0 The pr aims to upgrade `commons-text` from `1.10.0` to `1.11.0`. Release note: https://commons.apache.org/proper/commons-text/changes-report.html#a1.11.0 includes some bug fix, eg: - Fix StringTokenizer.getTokenList to return an independent modifiable list. Fixes [TEXT-219](https://issues.apache.org/jira/browse/TEXT-219). - Fix TextStringBuilder to over-allocate when ensuring capacity apache#452. Fixes [TEXT-228](https://issues.apache.org/jira/browse/TEXT-228). - TextStringBuidler#hashCode() allocates a String on each call apache#387. No. Pass GA. No. Closes apache#43590 from panbingkun/SPARK-45732. Authored-by: panbingkun <[email protected]> Signed-off-by: Hyukjin Kwon <[email protected]> (cherry picked from commit d38f074) [SPARK-40801][BUILD] Upgrade `Apache commons-text` to 1.10 Upgrade Apache commons-text from 1.9 to 1.10.0 [CVE-2022-42889](https://nvd.nist.gov/vuln/detail/CVE-2022-42889) No. Pass github action Closes apache#38262 from bjornjorgensen/commons-text-1.10. Authored-by: Bjørn <[email protected]> Signed-off-by: Yuming Wang <[email protected]> (cherry picked from commit 99abc94) [SPARK-38231][BUILD] Upgrade commons-text to 1.9 This PR aims to upgrade commons-text to 1.9. 1.9 is the latest and popular than 1.6. - https://commons.apache.org/proper/commons-text/changes-report.html#a1.9 - https://mvnrepository.com/artifact/org.apache.commons/commons-text No Pass GA Closes apache#35542 from LuciferYang/upgrade-common-text. Authored-by: yangjie01 <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 70f5bfd) (cherry picked from commit 5cb61e7) # Conflicts: # pom.xml * ODP-1302 [SPARK-43225][BUILD][SQL] Remove jackson-core-asl and jackson-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml --------- Co-authored-by: Dongjoon Hyun <[email protected]> Co-authored-by: Yuming Wang <[email protected]>
senthh
pushed a commit
to acceldata-io/spark3
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Aug 14, 2024
…n-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml
senthh
pushed a commit
to acceldata-io/spark3
that referenced
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Sep 16, 2024
…n-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml
prabhjyotsingh
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Sep 18, 2024
…n-mapper-asl from pre-built distribution (#39) - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml Co-authored-by: Yuming Wang <[email protected]>
szehon-ho
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that referenced
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Sep 24, 2024
This PR aims to provide a new profile, `hive-jackson-provided`, for Apache Spark 4.0.0. Since Apache Hadoop 3.3.5, only Apache Hive requires old CodeHaus Jackson dependencies. Apache Spark 3.5.0 tried to eliminate them completely but it's reverted due to Hive UDF support. - apache#40893 - apache#42446 To allow Apache Spark 4.0 users - To provide their own CodeHaus Jackson libraries - To exclude them completely if they don't use `Hive UDF`. No, this is a new profile. Pass the CIs and manual build. **Without `hive-jackson-provided`** ``` $ dev/make-distribution.sh -Phive,hive-thriftserver $ ls -al dist/jars/*asl* -rw-r--r-- 1 dongjoon staff 232248 Feb 21 10:53 dist.org/jars/jackson-core-asl-1.9.13.jar -rw-r--r-- 1 dongjoon staff 780664 Feb 21 10:53 dist.org/jars/jackson-mapper-asl-1.9.13.jar ``` **With `hive-jackson-provided`** ``` $ dev/make-distribution.sh -Phive,hive-thriftserver,hive-jackson-provided $ ls -al dist/jars/*asl* zsh: no matches found: dist/jars/*asl* $ ls -al dist/jars/*hive* -rw-r--r-- 1 dongjoon staff 183633 Feb 21 11:00 dist/jars/hive-beeline-2.3.9.jar -rw-r--r-- 1 dongjoon staff 44704 Feb 21 11:00 dist/jars/hive-cli-2.3.9.jar -rw-r--r-- 1 dongjoon staff 436169 Feb 21 11:00 dist/jars/hive-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 10840949 Feb 21 11:00 dist/jars/hive-exec-2.3.9-core.jar -rw-r--r-- 1 dongjoon staff 116364 Feb 21 11:00 dist/jars/hive-jdbc-2.3.9.jar -rw-r--r-- 1 dongjoon staff 326585 Feb 21 11:00 dist/jars/hive-llap-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 8195966 Feb 21 11:00 dist/jars/hive-metastore-2.3.9.jar -rw-r--r-- 1 dongjoon staff 916630 Feb 21 11:00 dist/jars/hive-serde-2.3.9.jar -rw-r--r-- 1 dongjoon staff 1679366 Feb 21 11:00 dist/jars/hive-service-rpc-3.1.3.jar -rw-r--r-- 1 dongjoon staff 53902 Feb 21 11:00 dist/jars/hive-shims-0.23-2.3.9.jar -rw-r--r-- 1 dongjoon staff 8786 Feb 21 11:00 dist/jars/hive-shims-2.3.9.jar -rw-r--r-- 1 dongjoon staff 120293 Feb 21 11:00 dist/jars/hive-shims-common-2.3.9.jar -rw-r--r-- 1 dongjoon staff 12923 Feb 21 11:00 dist/jars/hive-shims-scheduler-2.3.9.jar -rw-r--r-- 1 dongjoon staff 258346 Feb 21 11:00 dist/jars/hive-storage-api-2.8.1.jar -rw-r--r-- 1 dongjoon staff 581739 Feb 21 11:00 dist/jars/spark-hive-thriftserver_2.13-4.0.0-SNAPSHOT.jar -rw-r--r-- 1 dongjoon staff 687446 Feb 21 11:00 dist/jars/spark-hive_2.13-4.0.0-SNAPSHOT.jar ``` No. Closes apache#45201 from dongjoon-hyun/SPARK-47119. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
senthh
added a commit
to acceldata-io/spark3
that referenced
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Nov 12, 2024
…n-mapper-asl from pre-built distribution (#39) - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml Co-authored-by: Yuming Wang <[email protected]>
senthh
pushed a commit
to acceldata-io/spark3
that referenced
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Nov 13, 2024
* ODP-1304 [SPARK-44914][BUILD] Upgrade Apache Ivy to 2.5.2 This PR aims to upgrade Apache Ivy to 2.5.2 and protect old Ivy-based systems like old Spark from Apache Ivy 2.5.2's incompatibility by introducing a new `.ivy2.5.2` directory. - Apache Spark 4.0.0 will create this once and reuse this directory while all the other systems like old Sparks uses the old one, `.ivy2`. So, the behavior is the same with the case where Apache Spark 4.0.0 is installed and used in a new machine. - For the environments with `User-provided Ivy-path`es, the user might hit the incompatibility still. However, the users can mitigate them because they already have full control on `Ivy-path`es. This was tried once and reverted logically due to Java 11 and Java 17 failures in Daily CIs. - apache#42613 - apache#42668 Currently, PR Builder also fails as of now. If the PR passes CIes, we can achieve the following. - [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) - FIX: CVE-2022-46751: Apache Ivy Is Vulnerable to XML External Entity Injections No. Pass the CIs including `HiveExternalCatalogVersionsSuite`. No. Closes apache#45075 from dongjoon-hyun/SPARK-44914. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 3baa60a) [SPARK-44968][BUILD] Downgrade ivy from 2.5.2 to 2.5.1 ### What changes were proposed in this pull request? After upgrading Ivy from 2.5.1 to 2.5.2 in SPARK-44914, daily tests for Java 11 and Java 17 began to experience ABORTED in the `HiveExternalCatalogVersionsSuite` test. Java 11 - https://github.com/apache/spark/actions/runs/5953716283/job/16148657660 - https://github.com/apache/spark/actions/runs/5966131923/job/16185159550 Java 17 - https://github.com/apache/spark/actions/runs/5956925790/job/16158714165 - https://github.com/apache/spark/actions/runs/5969348559/job/16195073478 ``` 2023-08-23T23:00:49.6547573Z [info] 2023-08-23 16:00:48.209 - stdout> : java.lang.RuntimeException: problem during retrieve of org.apache.spark#spark-submit-parent-4c061f04-b951-4d06-8909-cde5452988d9: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6548745Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:238) 2023-08-23T23:00:49.6549572Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:89) 2023-08-23T23:00:49.6550334Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.Ivy.retrieve(Ivy.java:551) 2023-08-23T23:00:49.6551079Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.deploy.SparkSubmitUtils$.resolveMavenCoordinates(SparkSubmit.scala:1464) 2023-08-23T23:00:49.6552024Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.$anonfun$downloadVersion$2(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6552884Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.util.package$.quietly(package.scala:42) 2023-08-23T23:00:49.6553755Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.downloadVersion(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6554705Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.liftedTree1$1(IsolatedClientLoader.scala:65) 2023-08-23T23:00:49.6555637Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.forVersion(IsolatedClientLoader.scala:64) 2023-08-23T23:00:49.6556554Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:443) 2023-08-23T23:00:49.6557340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:356) 2023-08-23T23:00:49.6558187Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client$lzycompute(HiveExternalCatalog.scala:71) 2023-08-23T23:00:49.6559061Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client(HiveExternalCatalog.scala:70) 2023-08-23T23:00:49.6559962Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$databaseExists$1(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6560766Z [info] 2023-08-23 16:00:48.209 - stdout> at scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23) 2023-08-23T23:00:49.6561584Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:102) 2023-08-23T23:00:49.6562510Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6563435Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:150) 2023-08-23T23:00:49.6564323Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:140) 2023-08-23T23:00:49.6565340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:45) 2023-08-23T23:00:49.6566321Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.$anonfun$catalog$1(HiveSessionStateBuilder.scala:60) 2023-08-23T23:00:49.6567363Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog$lzycompute(SessionCatalog.scala:118) 2023-08-23T23:00:49.6568372Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog(SessionCatalog.scala:118) 2023-08-23T23:00:49.6569393Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.tableExists(SessionCatalog.scala:490) 2023-08-23T23:00:49.6570685Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.CreateDataSourceTableAsSelectCommand.run(createDataSourceTables.scala:155) 2023-08-23T23:00:49.6571842Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113) 2023-08-23T23:00:49.6572932Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111) 2023-08-23T23:00:49.6573996Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125) 2023-08-23T23:00:49.6575045Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:97) 2023-08-23T23:00:49.6576066Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) 2023-08-23T23:00:49.6576937Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) 2023-08-23T23:00:49.6577807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) 2023-08-23T23:00:49.6578620Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6579432Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) 2023-08-23T23:00:49.6580357Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:97) 2023-08-23T23:00:49.6581331Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:93) 2023-08-23T23:00:49.6582239Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:481) 2023-08-23T23:00:49.6583101Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82) 2023-08-23T23:00:49.6584088Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:481) 2023-08-23T23:00:49.6585236Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6586519Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) 2023-08-23T23:00:49.6587686Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) 2023-08-23T23:00:49.6588898Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590014Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590993Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:457) 2023-08-23T23:00:49.6591930Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:93) 2023-08-23T23:00:49.6592914Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:80) 2023-08-23T23:00:49.6593856Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:78) 2023-08-23T23:00:49.6594687Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:219) 2023-08-23T23:00:49.6595379Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99) 2023-08-23T23:00:49.6596103Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6596807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:96) 2023-08-23T23:00:49.6597520Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:618) 2023-08-23T23:00:49.6598276Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6599022Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:613) 2023-08-23T23:00:49.6599819Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 2023-08-23T23:00:49.6600723Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77) 2023-08-23T23:00:49.6601707Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 2023-08-23T23:00:49.6602513Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.reflect.Method.invoke(Method.java:568) 2023-08-23T23:00:49.6603272Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) 2023-08-23T23:00:49.6604007Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) 2023-08-23T23:00:49.6604724Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.Gateway.invoke(Gateway.java:282) 2023-08-23T23:00:49.6605416Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) 2023-08-23T23:00:49.6606209Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.CallCommand.execute(CallCommand.java:79) 2023-08-23T23:00:49.6606969Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) 2023-08-23T23:00:49.6607743Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.run(ClientServerConnection.java:106) 2023-08-23T23:00:49.6608415Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.Thread.run(Thread.java:833) 2023-08-23T23:00:49.6609288Z [info] 2023-08-23 16:00:48.209 - stdout> Caused by: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6610288Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.determineArtifactsToCopy(RetrieveEngine.java:426) 2023-08-23T23:00:49.6611332Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:122) 2023-08-23T23:00:49.6612046Z [info] 2023-08-23 16:00:48.209 - stdout> ... 66 more 2023-08-23T23:00:49.6612498Z [info] 2023-08-23 16:00:48.209 - stdout> ``` So this pr downgrade ivy from 2.5.2 to 2.5.1 to restore Java 11/17 daily tests. ### Why are the changes needed? To restore Java 11/17 daily tests. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By changing the default Java version in `build_and_test.yml` to 17 for verification, the tests succeed after downgrading the Ivy to 2.5.1. - https://github.com/LuciferYang/spark/actions/runs/5972232677/job/16209970934 <img width="1116" alt="image" src="https://github.com/apache/spark/assets/1475305/cd4002d8-893d-4845-8b2e-c01ff3106f7f"> ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#42668 from LuciferYang/test-java17. Authored-by: yangjie01 <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 4f8a199) [SPARK-44914][BUILD] Upgrade `Apache ivy` from 2.5.1 to 2.5.2 Upgrade Apache ivy from 2.5.1 to 2.5.2 [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) [CVE-2022-46751](https://www.cve.org/CVERecord?id=CVE-2022-46751) The fix apache/ant-ivy@2be17bc No. Pass GA No. Closes apache#42613 from bjornjorgensen/ivy-2.5.2. Authored-by: Bjørn Jørgensen <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 611e17e) [SPARK-41030][BUILD] Upgrade `Apache Ivy` to 2.5.1 Upgrade `Apache Ivy` from 2.5.0 to 2.5.1 [Release notes](https://ant.apache.org/ivy/history/2.5.1/release-notes.html) [CVE-2022-37865](https://www.cve.org/CVERecord?id=CVE-2022-37865) and [CVE-2022-37866](https://nvd.nist.gov/vuln/detail/CVE-2022-37866) No. Pass GA Closes apache#38539 from bjornjorgensen/ivy-2.5.1. Authored-by: Bjørn <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 4bbdca6) (cherry picked from commit 0e5fa79) # Conflicts: # dev/deps/spark-deps-hadoop-2-hive-2.3 # dev/deps/spark-deps-hadoop-3-hive-2.3 # docs/core-migration-guide.md # pom.xml * ODP-1303 [SPARK-45732][BUILD] Upgrade commons-text to 1.11.0 The pr aims to upgrade `commons-text` from `1.10.0` to `1.11.0`. Release note: https://commons.apache.org/proper/commons-text/changes-report.html#a1.11.0 includes some bug fix, eg: - Fix StringTokenizer.getTokenList to return an independent modifiable list. Fixes [TEXT-219](https://issues.apache.org/jira/browse/TEXT-219). - Fix TextStringBuilder to over-allocate when ensuring capacity apache#452. Fixes [TEXT-228](https://issues.apache.org/jira/browse/TEXT-228). - TextStringBuidler#hashCode() allocates a String on each call apache#387. No. Pass GA. No. Closes apache#43590 from panbingkun/SPARK-45732. Authored-by: panbingkun <[email protected]> Signed-off-by: Hyukjin Kwon <[email protected]> (cherry picked from commit d38f074) [SPARK-40801][BUILD] Upgrade `Apache commons-text` to 1.10 Upgrade Apache commons-text from 1.9 to 1.10.0 [CVE-2022-42889](https://nvd.nist.gov/vuln/detail/CVE-2022-42889) No. Pass github action Closes apache#38262 from bjornjorgensen/commons-text-1.10. Authored-by: Bjørn <[email protected]> Signed-off-by: Yuming Wang <[email protected]> (cherry picked from commit 99abc94) [SPARK-38231][BUILD] Upgrade commons-text to 1.9 This PR aims to upgrade commons-text to 1.9. 1.9 is the latest and popular than 1.6. - https://commons.apache.org/proper/commons-text/changes-report.html#a1.9 - https://mvnrepository.com/artifact/org.apache.commons/commons-text No Pass GA Closes apache#35542 from LuciferYang/upgrade-common-text. Authored-by: yangjie01 <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 70f5bfd) (cherry picked from commit 5cb61e7) # Conflicts: # pom.xml * ODP-1302 [SPARK-43225][BUILD][SQL] Remove jackson-core-asl and jackson-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml --------- Co-authored-by: Dongjoon Hyun <[email protected]> Co-authored-by: Yuming Wang <[email protected]>
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* ODP-1304 [SPARK-44914][BUILD] Upgrade Apache Ivy to 2.5.2 This PR aims to upgrade Apache Ivy to 2.5.2 and protect old Ivy-based systems like old Spark from Apache Ivy 2.5.2's incompatibility by introducing a new `.ivy2.5.2` directory. - Apache Spark 4.0.0 will create this once and reuse this directory while all the other systems like old Sparks uses the old one, `.ivy2`. So, the behavior is the same with the case where Apache Spark 4.0.0 is installed and used in a new machine. - For the environments with `User-provided Ivy-path`es, the user might hit the incompatibility still. However, the users can mitigate them because they already have full control on `Ivy-path`es. This was tried once and reverted logically due to Java 11 and Java 17 failures in Daily CIs. - apache#42613 - apache#42668 Currently, PR Builder also fails as of now. If the PR passes CIes, we can achieve the following. - [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) - FIX: CVE-2022-46751: Apache Ivy Is Vulnerable to XML External Entity Injections No. Pass the CIs including `HiveExternalCatalogVersionsSuite`. No. Closes apache#45075 from dongjoon-hyun/SPARK-44914. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 3baa60a) [SPARK-44968][BUILD] Downgrade ivy from 2.5.2 to 2.5.1 ### What changes were proposed in this pull request? After upgrading Ivy from 2.5.1 to 2.5.2 in SPARK-44914, daily tests for Java 11 and Java 17 began to experience ABORTED in the `HiveExternalCatalogVersionsSuite` test. Java 11 - https://github.com/apache/spark/actions/runs/5953716283/job/16148657660 - https://github.com/apache/spark/actions/runs/5966131923/job/16185159550 Java 17 - https://github.com/apache/spark/actions/runs/5956925790/job/16158714165 - https://github.com/apache/spark/actions/runs/5969348559/job/16195073478 ``` 2023-08-23T23:00:49.6547573Z [info] 2023-08-23 16:00:48.209 - stdout> : java.lang.RuntimeException: problem during retrieve of org.apache.spark#spark-submit-parent-4c061f04-b951-4d06-8909-cde5452988d9: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6548745Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:238) 2023-08-23T23:00:49.6549572Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:89) 2023-08-23T23:00:49.6550334Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.Ivy.retrieve(Ivy.java:551) 2023-08-23T23:00:49.6551079Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.deploy.SparkSubmitUtils$.resolveMavenCoordinates(SparkSubmit.scala:1464) 2023-08-23T23:00:49.6552024Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.$anonfun$downloadVersion$2(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6552884Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.util.package$.quietly(package.scala:42) 2023-08-23T23:00:49.6553755Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.downloadVersion(IsolatedClientLoader.scala:138) 2023-08-23T23:00:49.6554705Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.liftedTree1$1(IsolatedClientLoader.scala:65) 2023-08-23T23:00:49.6555637Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.client.IsolatedClientLoader$.forVersion(IsolatedClientLoader.scala:64) 2023-08-23T23:00:49.6556554Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:443) 2023-08-23T23:00:49.6557340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:356) 2023-08-23T23:00:49.6558187Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client$lzycompute(HiveExternalCatalog.scala:71) 2023-08-23T23:00:49.6559061Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.client(HiveExternalCatalog.scala:70) 2023-08-23T23:00:49.6559962Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$databaseExists$1(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6560766Z [info] 2023-08-23 16:00:48.209 - stdout> at scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23) 2023-08-23T23:00:49.6561584Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:102) 2023-08-23T23:00:49.6562510Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:224) 2023-08-23T23:00:49.6563435Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:150) 2023-08-23T23:00:49.6564323Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:140) 2023-08-23T23:00:49.6565340Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:45) 2023-08-23T23:00:49.6566321Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.hive.HiveSessionStateBuilder.$anonfun$catalog$1(HiveSessionStateBuilder.scala:60) 2023-08-23T23:00:49.6567363Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog$lzycompute(SessionCatalog.scala:118) 2023-08-23T23:00:49.6568372Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.externalCatalog(SessionCatalog.scala:118) 2023-08-23T23:00:49.6569393Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.tableExists(SessionCatalog.scala:490) 2023-08-23T23:00:49.6570685Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.CreateDataSourceTableAsSelectCommand.run(createDataSourceTables.scala:155) 2023-08-23T23:00:49.6571842Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113) 2023-08-23T23:00:49.6572932Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111) 2023-08-23T23:00:49.6573996Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125) 2023-08-23T23:00:49.6575045Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:97) 2023-08-23T23:00:49.6576066Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) 2023-08-23T23:00:49.6576937Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) 2023-08-23T23:00:49.6577807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) 2023-08-23T23:00:49.6578620Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6579432Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) 2023-08-23T23:00:49.6580357Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:97) 2023-08-23T23:00:49.6581331Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:93) 2023-08-23T23:00:49.6582239Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:481) 2023-08-23T23:00:49.6583101Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82) 2023-08-23T23:00:49.6584088Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:481) 2023-08-23T23:00:49.6585236Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6586519Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) 2023-08-23T23:00:49.6587686Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) 2023-08-23T23:00:49.6588898Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590014Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) 2023-08-23T23:00:49.6590993Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:457) 2023-08-23T23:00:49.6591930Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:93) 2023-08-23T23:00:49.6592914Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:80) 2023-08-23T23:00:49.6593856Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:78) 2023-08-23T23:00:49.6594687Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:219) 2023-08-23T23:00:49.6595379Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99) 2023-08-23T23:00:49.6596103Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6596807Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:96) 2023-08-23T23:00:49.6597520Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:618) 2023-08-23T23:00:49.6598276Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) 2023-08-23T23:00:49.6599022Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:613) 2023-08-23T23:00:49.6599819Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 2023-08-23T23:00:49.6600723Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77) 2023-08-23T23:00:49.6601707Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 2023-08-23T23:00:49.6602513Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.reflect.Method.invoke(Method.java:568) 2023-08-23T23:00:49.6603272Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) 2023-08-23T23:00:49.6604007Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) 2023-08-23T23:00:49.6604724Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.Gateway.invoke(Gateway.java:282) 2023-08-23T23:00:49.6605416Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) 2023-08-23T23:00:49.6606209Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.commands.CallCommand.execute(CallCommand.java:79) 2023-08-23T23:00:49.6606969Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) 2023-08-23T23:00:49.6607743Z [info] 2023-08-23 16:00:48.209 - stdout> at py4j.ClientServerConnection.run(ClientServerConnection.java:106) 2023-08-23T23:00:49.6608415Z [info] 2023-08-23 16:00:48.209 - stdout> at java.base/java.lang.Thread.run(Thread.java:833) 2023-08-23T23:00:49.6609288Z [info] 2023-08-23 16:00:48.209 - stdout> Caused by: java.lang.RuntimeException: Multiple artifacts of the module log4j#log4j;1.2.17 are retrieved to the same file! Update the retrieve pattern to fix this error. 2023-08-23T23:00:49.6610288Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.determineArtifactsToCopy(RetrieveEngine.java:426) 2023-08-23T23:00:49.6611332Z [info] 2023-08-23 16:00:48.209 - stdout> at org.apache.ivy.core.retrieve.RetrieveEngine.retrieve(RetrieveEngine.java:122) 2023-08-23T23:00:49.6612046Z [info] 2023-08-23 16:00:48.209 - stdout> ... 66 more 2023-08-23T23:00:49.6612498Z [info] 2023-08-23 16:00:48.209 - stdout> ``` So this pr downgrade ivy from 2.5.2 to 2.5.1 to restore Java 11/17 daily tests. ### Why are the changes needed? To restore Java 11/17 daily tests. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By changing the default Java version in `build_and_test.yml` to 17 for verification, the tests succeed after downgrading the Ivy to 2.5.1. - https://github.com/LuciferYang/spark/actions/runs/5972232677/job/16209970934 <img width="1116" alt="image" src="https://github.com/apache/spark/assets/1475305/cd4002d8-893d-4845-8b2e-c01ff3106f7f"> ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#42668 from LuciferYang/test-java17. Authored-by: yangjie01 <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 4f8a199) [SPARK-44914][BUILD] Upgrade `Apache ivy` from 2.5.1 to 2.5.2 Upgrade Apache ivy from 2.5.1 to 2.5.2 [Release notes](https://lists.apache.org/thread/9gcz4xrsn8c7o9gb377xfzvkb8jltffr) [CVE-2022-46751](https://www.cve.org/CVERecord?id=CVE-2022-46751) The fix apache/ant-ivy@2be17bc No. Pass GA No. Closes apache#42613 from bjornjorgensen/ivy-2.5.2. Authored-by: Bjørn Jørgensen <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 611e17e) [SPARK-41030][BUILD] Upgrade `Apache Ivy` to 2.5.1 Upgrade `Apache Ivy` from 2.5.0 to 2.5.1 [Release notes](https://ant.apache.org/ivy/history/2.5.1/release-notes.html) [CVE-2022-37865](https://www.cve.org/CVERecord?id=CVE-2022-37865) and [CVE-2022-37866](https://nvd.nist.gov/vuln/detail/CVE-2022-37866) No. Pass GA Closes apache#38539 from bjornjorgensen/ivy-2.5.1. Authored-by: Bjørn <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 4bbdca6) (cherry picked from commit 0e5fa79) # Conflicts: # dev/deps/spark-deps-hadoop-2-hive-2.3 # dev/deps/spark-deps-hadoop-3-hive-2.3 # docs/core-migration-guide.md # pom.xml * ODP-1303 [SPARK-45732][BUILD] Upgrade commons-text to 1.11.0 The pr aims to upgrade `commons-text` from `1.10.0` to `1.11.0`. Release note: https://commons.apache.org/proper/commons-text/changes-report.html#a1.11.0 includes some bug fix, eg: - Fix StringTokenizer.getTokenList to return an independent modifiable list. Fixes [TEXT-219](https://issues.apache.org/jira/browse/TEXT-219). - Fix TextStringBuilder to over-allocate when ensuring capacity apache#452. Fixes [TEXT-228](https://issues.apache.org/jira/browse/TEXT-228). - TextStringBuidler#hashCode() allocates a String on each call apache#387. No. Pass GA. No. Closes apache#43590 from panbingkun/SPARK-45732. Authored-by: panbingkun <[email protected]> Signed-off-by: Hyukjin Kwon <[email protected]> (cherry picked from commit d38f074) [SPARK-40801][BUILD] Upgrade `Apache commons-text` to 1.10 Upgrade Apache commons-text from 1.9 to 1.10.0 [CVE-2022-42889](https://nvd.nist.gov/vuln/detail/CVE-2022-42889) No. Pass github action Closes apache#38262 from bjornjorgensen/commons-text-1.10. Authored-by: Bjørn <[email protected]> Signed-off-by: Yuming Wang <[email protected]> (cherry picked from commit 99abc94) [SPARK-38231][BUILD] Upgrade commons-text to 1.9 This PR aims to upgrade commons-text to 1.9. 1.9 is the latest and popular than 1.6. - https://commons.apache.org/proper/commons-text/changes-report.html#a1.9 - https://mvnrepository.com/artifact/org.apache.commons/commons-text No Pass GA Closes apache#35542 from LuciferYang/upgrade-common-text. Authored-by: yangjie01 <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]> (cherry picked from commit 70f5bfd) (cherry picked from commit 5cb61e7) # Conflicts: # pom.xml * ODP-1302 [SPARK-43225][BUILD][SQL] Remove jackson-core-asl and jackson-mapper-asl from pre-built distribution - Remove `jackson-core-asl` from maven dependency. - Change the scope of `jackson-mapper-asl` from compile to test. - Replace all `Hive.get(conf)` with `Hive.getWithoutRegisterFns(conf)`. To fix CVE issue: https://github.com/apache/spark/security/dependabot/50. No. manual test. Closes apache#40893 from wangyum/SPARK-43225. Lead-authored-by: Yuming Wang <[email protected]> Co-authored-by: Yuming Wang <[email protected]> Signed-off-by: Sean Owen <[email protected]> (cherry picked from commit 9c237d7) [SPARK-43868][SQL][TESTS] Remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action This pr remove `originalUDFs` from `TestHive` to ensure `ObjectHashAggregateExecBenchmark` can run successfully on Github Action. After SPARK-43225, `org.codehaus.jackson:jackson-mapper-asl` becomes a test scope dependency, so when using GA to run benchmark, it is not in the classpath because GA uses https://github.com/apache/spark/blob/d61c77cac17029ee27319e6b766b48d314a4dd31/.github/workflows/benchmark.yml#L179-L183 iunstead of the sbt `Test/runMain`. `ObjectHashAggregateExecBenchmark` used `TestHive`, and `TestHive` will always call `org.apache.hadoop.hive.ql.exec.FunctionRegistry#getFunctionNames` to init `originalUDFs` before this pr, so when we run `ObjectHashAggregateExecBenchmark` on GitHub Actions, there will be the following exceptions: (cherry picked from commit 1c10e28) # Conflicts: # pom.xml --------- Co-authored-by: Dongjoon Hyun <[email protected]> Co-authored-by: Yuming Wang <[email protected]>
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HI @pan3793 @dongjoon-hyun . Since, the spark 4.0.0 has been upgraded to hive 2.3.10 and hadoop 3.3.6. Cant we now implement this change back to remove jackson-mapper-asl and jackson-core-asl from pre-built distribution |
Member
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Hi, @Madhukar525722 . No, we can't because the existing users have Hive UDF jars which are built against old Hive 2.3.9 and older. Technically, we cannot enforce Apache Spark users to rebuilt every Hive UDF jars in their company. Actually, no user wants to rebuild all their Hive UDF jars against on newly arrived Hive 2.3.10.
However, Apache Spark community provides an alternative way in order to remove them from
Here are the difference between Apache Spark 4.0.0-preview2 and Apache Spark 3.5.4 . Please try to use Apache Spark 4.0.0-preview2 and let us know your pain point, @Madhukar525722 . |
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Hi @dongjoon-hyun |
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@Madhukar525722 I think either upgrading Hive 2.3.10 or applying SPARK-51466 should allow Spark to get rid of "SPARK-48231 Remove unused CodeHaus Jackson dependencies" is on the 4.1 roadmap. (I think it also could be done in 4.0, and we do remove them in our internal 4.0 distribution, but given 4.0.0 has reached RC3, might be too late) |
Member
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Yes, @pan3793's comment is correct with the current status. We need to revisit this at 4.1.0, @Madhukar525722 . |
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What changes were proposed in this pull request?
jackson-core-aslfrom maven dependency.jackson-mapper-aslfrom compile to test.Hive.get(conf)withHive.getWithoutRegisterFns(conf).Why are the changes needed?
To fix CVE issue: https://github.com/apache/spark/security/dependabot/50.
Does this PR introduce any user-facing change?
No.
How was this patch tested?
manual test.