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[WIP][SPARK-28152][SQL][2.4] Mapped ShortType to SMALLINT and FloatType to REAL for MsSqlServerDialect #25238
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14aecd8
[SPARK-27159][SQL] update mssql server dialect to support binary type
zhulipeng ad967f4
[SPARK-27168][SQL][TEST] Add docker integration test for MsSql server
zhulipeng 277fda0
[SPARK-28152][SQL] Mapped ShortType to SMALLINT and FloatType to REAL…
shivsood 4336d1c
[SPARK-27159][SQL] update mssql server dialect to support binary type
zhulipeng 73bb605
[SPARK-27168][SQL][TEST] Add docker integration test for MsSql server
zhulipeng 4f0fca0
[SPARK-28152][SQL] Mapped ShortType to SMALLINT and FloatType to REAL…
shivsood 7f7adc1
Merge branch 'float_byte_type_fix_24' of https://github.com/shivsood/…
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205 changes: 205 additions & 0 deletions
205
...egration-tests/src/test/scala/org/apache/spark/sql/jdbc/MsSqlServerIntegrationSuite.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,205 @@ | ||
| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one or more | ||
| * contributor license agreements. See the NOTICE file distributed with | ||
| * this work for additional information regarding copyright ownership. | ||
| * The ASF licenses this file to You under the Apache License, Version 2.0 | ||
| * (the "License"); you may not use this file except in compliance with | ||
| * the License. You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
|
|
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| package org.apache.spark.sql.jdbc | ||
|
|
||
| import java.math.BigDecimal | ||
| import java.sql.{Connection, Date, Timestamp} | ||
| import java.util.Properties | ||
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| import org.apache.spark.tags.DockerTest | ||
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| @DockerTest | ||
| class MsSqlServerIntegrationSuite extends DockerJDBCIntegrationSuite { | ||
| override val db = new DatabaseOnDocker { | ||
| override val imageName = "mcr.microsoft.com/mssql/server:2017-GA-ubuntu" | ||
| override val env = Map( | ||
| "SA_PASSWORD" -> "Sapass123", | ||
| "ACCEPT_EULA" -> "Y" | ||
| ) | ||
| override val usesIpc = false | ||
| override val jdbcPort: Int = 1433 | ||
|
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| override def getJdbcUrl(ip: String, port: Int): String = | ||
| s"jdbc:sqlserver://$ip:$port;user=sa;password=Sapass123;" | ||
|
|
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| override def getStartupProcessName: Option[String] = None | ||
| } | ||
|
|
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| override def dataPreparation(conn: Connection): Unit = { | ||
| conn.prepareStatement("CREATE TABLE tbl (x INT, y VARCHAR (50))").executeUpdate() | ||
| conn.prepareStatement("INSERT INTO tbl VALUES (42,'fred')").executeUpdate() | ||
| conn.prepareStatement("INSERT INTO tbl VALUES (17,'dave')").executeUpdate() | ||
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|
||
| conn.prepareStatement( | ||
| """ | ||
| |CREATE TABLE numbers ( | ||
| |a BIT, | ||
| |b TINYINT, c SMALLINT, d INT, e BIGINT, | ||
| |f FLOAT, f1 FLOAT(24), | ||
| |g REAL, | ||
| |h DECIMAL(5,2), i NUMERIC(10,5), | ||
| |j MONEY, k SMALLMONEY) | ||
| """.stripMargin).executeUpdate() | ||
| conn.prepareStatement( | ||
| """ | ||
| |INSERT INTO numbers VALUES ( | ||
| |0, | ||
| |255, 32767, 2147483647, 9223372036854775807, | ||
| |123456789012345.123456789012345, 123456789012345.123456789012345, | ||
| |123456789012345.123456789012345, | ||
| |123, 12345.12, | ||
| |922337203685477.58, 214748.3647) | ||
| """.stripMargin).executeUpdate() | ||
|
|
||
| conn.prepareStatement( | ||
| """ | ||
| |CREATE TABLE dates ( | ||
| |a DATE, b DATETIME, c DATETIME2, | ||
| |d DATETIMEOFFSET, e SMALLDATETIME, | ||
| |f TIME) | ||
| """.stripMargin).executeUpdate() | ||
| conn.prepareStatement( | ||
| """ | ||
| |INSERT INTO dates VALUES ( | ||
| |'1991-11-09', '1999-01-01 13:23:35', '9999-12-31 23:59:59', | ||
| |'1901-05-09 23:59:59 +14:00', '1996-01-01 23:23:45', | ||
| |'13:31:24') | ||
| """.stripMargin).executeUpdate() | ||
|
|
||
| conn.prepareStatement( | ||
| """ | ||
| |CREATE TABLE strings ( | ||
| |a CHAR(10), b VARCHAR(10), | ||
| |c NCHAR(10), d NVARCHAR(10), | ||
| |e BINARY(4), f VARBINARY(4), | ||
| |g TEXT, h NTEXT, | ||
| |i IMAGE) | ||
| """.stripMargin).executeUpdate() | ||
| conn.prepareStatement( | ||
| """ | ||
| |INSERT INTO strings VALUES ( | ||
| |'the', 'quick', | ||
| |'brown', 'fox', | ||
| |123456, 123456, | ||
| |'the', 'lazy', | ||
| |'dog') | ||
| """.stripMargin).executeUpdate() | ||
| } | ||
|
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||
| test("Basic test") { | ||
| val df = spark.read.jdbc(jdbcUrl, "tbl", new Properties) | ||
| val rows = df.collect() | ||
| assert(rows.length == 2) | ||
| val types = rows(0).toSeq.map(x => x.getClass.toString) | ||
| assert(types.length == 2) | ||
| assert(types(0).equals("class java.lang.Integer")) | ||
| assert(types(1).equals("class java.lang.String")) | ||
| } | ||
|
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||
| test("Numeric types") { | ||
| val df = spark.read.jdbc(jdbcUrl, "numbers", new Properties) | ||
| val rows = df.collect() | ||
| assert(rows.length == 1) | ||
| val row = rows(0) | ||
| val types = row.toSeq.map(x => x.getClass.toString) | ||
| assert(types.length == 12) | ||
| assert(types(0).equals("class java.lang.Boolean")) | ||
| assert(types(1).equals("class java.lang.Integer")) | ||
| assert(types(2).equals("class java.lang.Short")) | ||
| assert(types(3).equals("class java.lang.Integer")) | ||
| assert(types(4).equals("class java.lang.Long")) | ||
| assert(types(5).equals("class java.lang.Double")) | ||
| assert(types(6).equals("class java.lang.Float")) | ||
| assert(types(7).equals("class java.lang.Float")) | ||
| assert(types(8).equals("class java.math.BigDecimal")) | ||
| assert(types(9).equals("class java.math.BigDecimal")) | ||
| assert(types(10).equals("class java.math.BigDecimal")) | ||
| assert(types(11).equals("class java.math.BigDecimal")) | ||
| assert(row.getBoolean(0) == false) | ||
| assert(row.getInt(1) == 255) | ||
| assert(row.getShort(2) == 32767) | ||
| assert(row.getInt(3) == 2147483647) | ||
| assert(row.getLong(4) == 9223372036854775807L) | ||
| assert(row.getDouble(5) == 1.2345678901234512E14) // float = float(53) has 15-digits precision | ||
| assert(row.getFloat(6) == 1.23456788103168E14) // float(24) has 7-digits precision | ||
| assert(row.getFloat(7) == 1.23456788103168E14) // real = float(24) | ||
| assert(row.getAs[BigDecimal](8).equals(new BigDecimal("123.00"))) | ||
| assert(row.getAs[BigDecimal](9).equals(new BigDecimal("12345.12000"))) | ||
| assert(row.getAs[BigDecimal](10).equals(new BigDecimal("922337203685477.5800"))) | ||
| assert(row.getAs[BigDecimal](11).equals(new BigDecimal("214748.3647"))) | ||
| } | ||
|
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||
| test("Date types") { | ||
| val df = spark.read.jdbc(jdbcUrl, "dates", new Properties) | ||
| val rows = df.collect() | ||
| assert(rows.length == 1) | ||
| val row = rows(0) | ||
| val types = row.toSeq.map(x => x.getClass.toString) | ||
| assert(types.length == 6) | ||
| assert(types(0).equals("class java.sql.Date")) | ||
| assert(types(1).equals("class java.sql.Timestamp")) | ||
| assert(types(2).equals("class java.sql.Timestamp")) | ||
| assert(types(3).equals("class java.lang.String")) | ||
| assert(types(4).equals("class java.sql.Timestamp")) | ||
| assert(types(5).equals("class java.sql.Timestamp")) | ||
| assert(row.getAs[Date](0).equals(Date.valueOf("1991-11-09"))) | ||
| assert(row.getAs[Timestamp](1).equals(Timestamp.valueOf("1999-01-01 13:23:35.0"))) | ||
| assert(row.getAs[Timestamp](2).equals(Timestamp.valueOf("9999-12-31 23:59:59.0"))) | ||
| assert(row.getString(3).equals("1901-05-09 23:59:59.0000000 +14:00")) | ||
| assert(row.getAs[Timestamp](4).equals(Timestamp.valueOf("1996-01-01 23:24:00.0"))) | ||
| assert(row.getAs[Timestamp](5).equals(Timestamp.valueOf("1900-01-01 13:31:24.0"))) | ||
| } | ||
|
|
||
| test("String types") { | ||
| val df = spark.read.jdbc(jdbcUrl, "strings", new Properties) | ||
| val rows = df.collect() | ||
| assert(rows.length == 1) | ||
| val row = rows(0) | ||
| val types = row.toSeq.map(x => x.getClass.toString) | ||
| assert(types.length == 9) | ||
| assert(types(0).equals("class java.lang.String")) | ||
| assert(types(1).equals("class java.lang.String")) | ||
| assert(types(2).equals("class java.lang.String")) | ||
| assert(types(3).equals("class java.lang.String")) | ||
| assert(types(4).equals("class [B")) | ||
| assert(types(5).equals("class [B")) | ||
| assert(types(6).equals("class java.lang.String")) | ||
| assert(types(7).equals("class java.lang.String")) | ||
| assert(types(8).equals("class [B")) | ||
| assert(row.getString(0).length == 10) | ||
| assert(row.getString(0).trim.equals("the")) | ||
| assert(row.getString(1).equals("quick")) | ||
| assert(row.getString(2).length == 10) | ||
| assert(row.getString(2).trim.equals("brown")) | ||
| assert(row.getString(3).equals("fox")) | ||
| assert(java.util.Arrays.equals(row.getAs[Array[Byte]](4), Array[Byte](0, 1, -30, 64))) | ||
| assert(java.util.Arrays.equals(row.getAs[Array[Byte]](5), Array[Byte](0, 1, -30, 64))) | ||
| assert(row.getString(6).equals("the")) | ||
| assert(row.getString(7).equals("lazy")) | ||
| assert(java.util.Arrays.equals(row.getAs[Array[Byte]](8), Array[Byte](100, 111, 103))) | ||
| } | ||
|
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| test("Basic write test") { | ||
| val df1 = spark.read.jdbc(jdbcUrl, "numbers", new Properties) | ||
| val df2 = spark.read.jdbc(jdbcUrl, "dates", new Properties) | ||
| val df3 = spark.read.jdbc(jdbcUrl, "strings", new Properties) | ||
| df1.write.jdbc(jdbcUrl, "numberscopy", new Properties) | ||
| df2.write.jdbc(jdbcUrl, "datescopy", new Properties) | ||
| df3.write.jdbc(jdbcUrl, "stringscopy", new Properties) | ||
| } | ||
| } |
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Okay. Since this is the same with
master, we can ignore adding JIRA ID.Uh oh!
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Are you referring to "test("MsSqlServerDialect jdbc type mapping")"? The fix updated this function, did not create a new function. For the new function that i added, i have mentioned the JIRA ID.
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That's exactly what I meant, @shivsood . The above comment is not about requesting changes. It was supporting your code. Usually, reviewers leave their comments for this other reviewers.
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Thanks