Consolidate TaskDescrition constructors. #2
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This commit also does all task serializion in the encode() method, so now the encode() method just takes the TaskDescription as an input parameter.
witgo
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## What changes were proposed in this pull request? There were two related fixes regarding `from_json`, `get_json_object` and `json_tuple` ([Fix #1](apache@c8803c0), [Fix #2](apache@86174ea)), but they weren't comprehensive it seems. I wanted to extend those fixes to all the parsers, and add tests for each case. ## How was this patch tested? Regression tests Author: Burak Yavuz <[email protected]> Closes apache#20302 from brkyvz/json-invfix.
witgo
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Sep 7, 2018
## What changes were proposed in this pull request? There were two related fixes regarding `from_json`, `get_json_object` and `json_tuple` ([Fix #1](apache@c8803c0), [Fix #2](apache@86174ea)), but they weren't comprehensive it seems. I wanted to extend those fixes to all the parsers, and add tests for each case. ## How was this patch tested? Regression tests Author: Burak Yavuz <[email protected]> Closes apache#20302 from brkyvz/json-invfix. (cherry picked from commit e01919e) Signed-off-by: hyukjinkwon <[email protected]>
witgo
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Jan 2, 2020
### What changes were proposed in this pull request? `org.apache.spark.sql.kafka010.KafkaDelegationTokenSuite` failed lately. After had a look at the logs it just shows the following fact without any details: ``` Caused by: sbt.ForkMain$ForkError: sun.security.krb5.KrbException: Server not found in Kerberos database (7) - Server not found in Kerberos database ``` Since the issue is intermittent and not able to reproduce it we should add more debug information and wait for reproduction with the extended logs. ### Why are the changes needed? Failing test doesn't give enough debug information. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? I've started the test manually and checked that such additional debug messages show up: ``` >>> KrbApReq: APOptions are 00000000 00000000 00000000 00000000 >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType Looking for keys for: kafka/localhostEXAMPLE.COM Added key: 17version: 0 Added key: 23version: 0 Added key: 16version: 0 Found unsupported keytype (3) for kafka/localhostEXAMPLE.COM >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType Using builtin default etypes for permitted_enctypes default etypes for permitted_enctypes: 17 16 23. >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType MemoryCache: add 1571936500/174770/16C565221B70AAB2BEFE31A83D13A2F4/client/localhostEXAMPLE.COM to client/localhostEXAMPLE.COM|kafka/localhostEXAMPLE.COM MemoryCache: Existing AuthList: apache#3: 1571936493/200803/8CD70D280B0862C5DA1FF901ECAD39FE/client/localhostEXAMPLE.COM #2: 1571936499/985009/BAD33290D079DD4E3579A8686EC326B7/client/localhostEXAMPLE.COM #1: 1571936499/995208/B76B9D78A9BE283AC78340157107FD40/client/localhostEXAMPLE.COM ``` Closes apache#26252 from gaborgsomogyi/SPARK-29580. Authored-by: Gabor Somogyi <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>
witgo
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Oct 7, 2024
… throw internal error
### What changes were proposed in this pull request?
This PR fixes the error messages and classes when Python UDFs are used in higher order functions.
### Why are the changes needed?
To show the proper user-facing exceptions with error classes.
### Does this PR introduce _any_ user-facing change?
Yes, previously it threw internal error such as:
```python
from pyspark.sql.functions import transform, udf, col, array
spark.range(1).select(transform(array("id"), lambda x: udf(lambda y: y)(x))).collect()
```
Before:
```
py4j.protocol.Py4JJavaError: An error occurred while calling o74.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 15 in stage 0.0 failed 1 times, most recent failure: Lost task 15.0 in stage 0.0 (TID 15) (ip-192-168-123-103.ap-northeast-2.compute.internal executor driver): org.apache.spark.SparkException: [INTERNAL_ERROR] Cannot evaluate expression: <lambda>(lambda x_0#3L)#2 SQLSTATE: XX000
at org.apache.spark.SparkException$.internalError(SparkException.scala:92)
at org.apache.spark.SparkException$.internalError(SparkException.scala:96)
```
After:
```
pyspark.errors.exceptions.captured.AnalysisException: [INVALID_LAMBDA_FUNCTION_CALL.UNEVALUABLE] Invalid lambda function call. Python UDFs should be used in a lambda function at a higher order function. However, "<lambda>(lambda x_0#3L)" was a Python UDF. SQLSTATE: 42K0D;
Project [transform(array(id#0L), lambdafunction(<lambda>(lambda x_0#3L)#2, lambda x_0#3L, false)) AS transform(array(id), lambdafunction(<lambda>(lambda x_0#3L), namedlambdavariable()))apache#4]
+- Range (0, 1, step=1, splits=Some(16))
```
### How was this patch tested?
Unittest was added
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes apache#47079 from HyukjinKwon/SPARK-48706.
Authored-by: Hyukjin Kwon <[email protected]>
Signed-off-by: Kent Yao <[email protected]>
witgo
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Jan 5, 2025
### What changes were proposed in this pull request? Fix self-join after `applyInArrow`, the same issue of `applyInPandas` was fixed in apache#31429 ### Why are the changes needed? bug fix before: ``` In [1]: import pyarrow as pa In [2]: df = spark.createDataFrame([(1, 1)], ("k", "v")) In [3]: def arrow_func(key, table): ...: return pa.Table.from_pydict({"x": [2], "y": [2]}) ...: In [4]: df2 = df.groupby("k").applyInArrow(arrow_func, schema="x long, y long") In [5]: df2.show() 24/12/04 17:47:43 WARN CheckAllocator: More than one DefaultAllocationManager on classpath. Choosing first found +---+---+ | x| y| +---+---+ | 2| 2| +---+---+ In [6]: df2.join(df2) ... Failure when resolving conflicting references in Join: 'Join Inner :- FlatMapGroupsInArrow [k#0L], arrow_func(k#0L, v#1L)#2, [x#3L, y#4L] : +- Project [k#0L, k#0L, v#1L] : +- LogicalRDD [k#0L, v#1L], false +- FlatMapGroupsInArrow [k#12L], arrow_func(k#12L, v#13L)#2, [x#3L, y#4L] +- Project [k#12L, k#12L, v#13L] +- LogicalRDD [k#12L, v#13L], false Conflicting attributes: "x", "y". SQLSTATE: XX000 at org.apache.spark.SparkException$.internalError(SparkException.scala:92) at org.apache.spark.SparkException$.internalError(SparkException.scala:79) at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$2(CheckAnalysis.scala:798) ``` after: ``` In [6]: df2.join(df2) Out[6]: DataFrame[x: bigint, y: bigint, x: bigint, y: bigint] In [7]: df2.join(df2).show() +---+---+---+---+ | x| y| x| y| +---+---+---+---+ | 2| 2| 2| 2| +---+---+---+---+ ``` ### Does this PR introduce _any_ user-facing change? bug fix ### How was this patch tested? added tests ### Was this patch authored or co-authored using generative AI tooling? no Closes apache#49056 from zhengruifeng/fix_arrow_join. Authored-by: Ruifeng Zheng <[email protected]> Signed-off-by: Hyukjin Kwon <[email protected]>
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Here's what I was thinking in the PR -- let me know if this makes sense.