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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2018/11/20 10:50:00 UTC
[jira] [Assigned] (SPARK-26077) Reserved SQL words are not escaped
by JDBC writer for table name
[ https://issues.apache.org/jira/browse/SPARK-26077?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-26077:
------------------------------------
Assignee: Apache Spark
> Reserved SQL words are not escaped by JDBC writer for table name
> ----------------------------------------------------------------
>
> Key: SPARK-26077
> URL: https://issues.apache.org/jira/browse/SPARK-26077
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.3.2
> Reporter: Eugene Golovan
> Assignee: Apache Spark
> Priority: Major
>
> This bug is similar to SPARK-16387 but this time table name is not escaped.
> How to reproduce:
> 1/ Start spark shell with mysql connector
> spark-shell --jars ./mysql-connector-java-8.0.13.jar
>
> 2/ Execute next code
>
> import spark.implicits._
> (spark
> .createDataset(Seq("a","b","c"))
> .toDF("order")
> .write
> .format("jdbc")
> .option("url", s"jdbc:mysql://root@localhost:3306/test")
> .option("driver", "com.mysql.cj.jdbc.Driver")
> .option("dbtable", "condition")
> .save)
>
> , where condition - is reserved word.
>
> Error message:
>
> java.sql.SQLSyntaxErrorException: You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near 'condition (`order` TEXT )' at line 1
> at com.mysql.cj.jdbc.exceptions.SQLError.createSQLException(SQLError.java:120)
> at com.mysql.cj.jdbc.exceptions.SQLError.createSQLException(SQLError.java:97)
> at com.mysql.cj.jdbc.exceptions.SQLExceptionsMapping.translateException(SQLExceptionsMapping.java:122)
> at com.mysql.cj.jdbc.StatementImpl.executeUpdateInternal(StatementImpl.java:1355)
> at com.mysql.cj.jdbc.StatementImpl.executeLargeUpdate(StatementImpl.java:2128)
> at com.mysql.cj.jdbc.StatementImpl.executeUpdate(StatementImpl.java:1264)
> at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.createTable(JdbcUtils.scala:844)
> at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:95)
> at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
> at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
> at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
> at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
> at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
> at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
> at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656)
> at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656)
> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
> at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:656)
> at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273)
> at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267)
> ... 59 elided
>
>
>
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