Hello, I am trying to write from a python spark data-frame that contains mainly integers, strings and array of strings to crate through the jdbc standalone driver. When I execute the command I get:
IllegalArgumentException: Can't get JDBC type for array<string>
Any help is appreciated, thanks!
Update:
I guess this is related to a compatibility structure type, therefore I converted the array into a string but I am getting now this error:
Py4JJavaError: An error occurred while calling o354.jdbc.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1) (df72f42a513d executor driver): java.lang.IllegalArgumentException: Can't change resolved type for param: 16 from 26 to 23
at io.crate.shade.org.postgresql.core.v3.SimpleParameterList.setResolvedType(SimpleParameterList.java:313)
at io.crate.shade.org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:1985)
at io.crate.shade.org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:308)
at io.crate.shade.org.postgresql.jdbc.PgStatement.executeBatch(PgStatement.java:819)
at io.crate.shade.org.postgresql.jdbc.PgPreparedStatement.executeBatch(PgPreparedStatement.java:1497)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:687)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1(JdbcUtils.scala:856)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1$adapted(JdbcUtils.scala:854)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1020)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1020)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2236)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:829)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2258)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2207)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2206)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2206)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1079)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1079)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1079)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2445)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2387)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2376)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2196)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2217)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2236)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2261)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$1(RDD.scala:1020)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:1018)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.saveTable(JdbcUtils.scala:854)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:68)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
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:90)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:180)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:218)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:215)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:176)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:132)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:131)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301)
at org.apache.spark.sql.DataFrameWriter.jdbc(DataFrameWriter.scala:817)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: java.lang.IllegalArgumentException: Can't change resolved type for param: 16 from 26 to 23
at io.crate.shade.org.postgresql.core.v3.SimpleParameterList.setResolvedType(SimpleParameterList.java:313)
at io.crate.shade.org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:1985)
at io.crate.shade.org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:308)
at io.crate.shade.org.postgresql.jdbc.PgStatement.executeBatch(PgStatement.java:819)
at io.crate.shade.org.postgresql.jdbc.PgPreparedStatement.executeBatch(PgPreparedStatement.java:1497)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:687)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1(JdbcUtils.scala:856)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1$adapted(JdbcUtils.scala:854)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1020)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1020)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2236)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
... 1 more
And if I try to use the PostgreSQL driver:
Py4JJavaError: An error occurred while calling o351.jdbc.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1) (df72f42a513d executor driver): org.postgresql.util.PSQLException: ERROR: line 1:1: mismatched input 'ROLLBACK' expecting {'SELECT', 'DEALLOCATE', 'CREATE', 'ALTER', 'KILL', 'BEGIN', 'COMMIT', 'ANALYZE', 'DISCARD', 'EXPLAIN', 'SHOW', 'OPTIMIZE', 'REFRESH', 'RESTORE', 'DROP', 'INSERT', 'VALUES', 'DELETE', 'UPDATE', 'SET', 'RESET', 'COPY', 'GRANT', 'DENY', 'REVOKE'}
at org.postgresql.core.v3.QueryExecutorImpl.receiveErrorResponse(QueryExecutorImpl.java:2552)
at org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2284)
at org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:322)
at org.postgresql.jdbc.PgConnection.executeTransactionCommand(PgConnection.java:849)
at org.postgresql.jdbc.PgConnection.rollback(PgConnection.java:892)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:727)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1(JdbcUtils.scala:856)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1$adapted(JdbcUtils.scala:854)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1020)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1020)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2236)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: org.postgresql.util.PSQLException: ERROR: Can't map PGType with oid=1042 to Crate type
at org.postgresql.core.v3.QueryExecutorImpl.receiveErrorResponse(QueryExecutorImpl.java:2552)
at org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2284)
at org.postgresql.core.v3.QueryExecutorImpl.flushIfDeadlockRisk(QueryExecutorImpl.java:1403)
at org.postgresql.core.v3.QueryExecutorImpl.sendQuery(QueryExecutorImpl.java:1428)
at org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:506)
at org.postgresql.jdbc.PgStatement.internalExecuteBatch(PgStatement.java:878)
at org.postgresql.jdbc.PgStatement.executeBatch(PgStatement.java:901)
at org.postgresql.jdbc.PgPreparedStatement.executeBatch(PgPreparedStatement.java:1644)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:687)
... 13 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2258)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2207)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2206)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2206)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1079)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1079)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1079)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2445)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2387)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2376)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2196)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2217)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2236)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2261)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$1(RDD.scala:1020)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:1018)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.saveTable(JdbcUtils.scala:854)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:82)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:180)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:218)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:215)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:176)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:132)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:131)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301)
at org.apache.spark.sql.DataFrameWriter.jdbc(DataFrameWriter.scala:817)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: org.postgresql.util.PSQLException: ERROR: line 1:1: mismatched input 'ROLLBACK' expecting {'SELECT', 'DEALLOCATE', 'CREATE', 'ALTER', 'KILL', 'BEGIN', 'COMMIT', 'ANALYZE', 'DISCARD', 'EXPLAIN', 'SHOW', 'OPTIMIZE', 'REFRESH', 'RESTORE', 'DROP', 'INSERT', 'VALUES', 'DELETE', 'UPDATE', 'SET', 'RESET', 'COPY', 'GRANT', 'DENY', 'REVOKE'}
at org.postgresql.core.v3.QueryExecutorImpl.receiveErrorResponse(QueryExecutorImpl.java:2552)
at org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2284)
at org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:322)
at org.postgresql.jdbc.PgConnection.executeTransactionCommand(PgConnection.java:849)
at org.postgresql.jdbc.PgConnection.rollback(PgConnection.java:892)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:727)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1(JdbcUtils.scala:856)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1$adapted(JdbcUtils.scala:854)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1020)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1020)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2236)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
... 1 more
Caused by: org.postgresql.util.PSQLException: ERROR: Can't map PGType with oid=1042 to Crate type
at org.postgresql.core.v3.QueryExecutorImpl.receiveErrorResponse(QueryExecutorImpl.java:2552)
at org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2284)
at org.postgresql.core.v3.QueryExecutorImpl.flushIfDeadlockRisk(QueryExecutorImpl.java:1403)
at org.postgresql.core.v3.QueryExecutorImpl.sendQuery(QueryExecutorImpl.java:1428)
at org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:506)
at org.postgresql.jdbc.PgStatement.internalExecuteBatch(PgStatement.java:878)
at org.postgresql.jdbc.PgStatement.executeBatch(PgStatement.java:901)
at org.postgresql.jdbc.PgPreparedStatement.executeBatch(PgPreparedStatement.java:1644)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:687)
... 13 more
Solution:
After try and error of different approaches, I finally can insert data into crate with the driver. While loading a csv, there will be cases that the cell is empty and spark’s dataframe will assign it with a None. This value will try to be inserted, hence the “Can’t change resolved type for param” message. Since the other cells contain a string, the None type is not recognized and it needs to be manually changed into an empty string.
JDBC driver works as expected.
