Я пытаюсь сравнить записи из кадра данных, полученного из Redshift, в столбце с одним литеральным значением. Когда я создаю свой собственный фрейм данных, следующее работает, но не с фреймом данных красного смещения
df_events.filter(df_events.user_id.like('')).show()
Если я выполняю команду, указанную выше, я получаю следующую ошибку, которую я не могу понять
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<command-646896113420045> in <module>()
----> 1 df_events.filter(df_events.user_id.like('')).show()
/databricks/spark/python/pyspark/sql/dataframe.py in show(self, n, truncate, vertical)
377 """
378 if isinstance(truncate, bool) and truncate:
--> 379 print(self._jdf.showString(n, 20, vertical))
380 else:
381 print(self._jdf.showString(n, int(truncate), vertical))
/databricks/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py in __call__(self, *args)
1255 answer = self.gateway_client.send_command(command)
1256 return_value = get_return_value(
-> 1257 answer, self.gateway_client, self.target_id, self.name)
1258
1259 for temp_arg in temp_args:
/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/databricks/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
Py4JJavaError: An error occurred while calling o2372.showString.
: java.sql.SQLException: Exception thrown in awaitResult:
at com.databricks.spark.redshift.JDBCWrapper.com$databricks$spark$redshift$JDBCWrapper$$executeInterruptibly(RedshiftJDBCWrapper.scala:213)
at com.databricks.spark.redshift.JDBCWrapper.executeInterruptibly(RedshiftJDBCWrapper.scala:187)
at com.databricks.spark.redshift.RedshiftRelation$$anonfun$getRDDFromS3$1.apply$mcZ$sp(RedshiftRelation.scala:199)
at com.databricks.spark.redshift.RedshiftRelation$$anonfun$getRDDFromS3$1.apply(RedshiftRelation.scala:199)
at com.databricks.spark.redshift.RedshiftRelation$$anonfun$getRDDFromS3$1.apply(RedshiftRelation.scala:199)
at com.databricks.backend.daemon.driver.ProgressReporter$.withStatusCode(ProgressReporter.scala:345)
at com.databricks.backend.daemon.driver.ProgressReporter$.withStatusCode(ProgressReporter.scala:331)
at com.databricks.spark.util.SparkDatabricksProgressReporter$.withStatusCode(ProgressReporter.scala:23)
at com.databricks.spark.redshift.RedshiftRelation.getRDDFromS3(RedshiftRelation.scala:198)
at com.databricks.spark.redshift.RedshiftRelation.buildScan(RedshiftRelation.scala:143)
at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$10.apply(DataSourceStrategy.scala:338)
at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$10.apply(DataSourceStrategy.scala:338)
at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$pruneFilterProject$1.apply(DataSourceStrategy.scala:372)
at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$pruneFilterProject$1.apply(DataSourceStrategy.scala:371)
at org.apache.spark.sql.execution.datasources.DataSourceStrategy.pruneFilterProjectRaw(DataSourceStrategy.scala:450)
at org.apache.spark.sql.execution.datasources.DataSourceStrategy.pruneFilterProject(DataSourceStrategy.scala:367)
at org.apache.spark.sql.execution.datasources.DataSourceStrategy.apply(DataSourceStrategy.scala:334)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:68)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:64)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:102)
at org.apache.spark.sql.execution.SparkStrategies.plan(SparkStrategies.scala:76)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$3.apply(QueryPlanner.scala:87)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$3.apply(QueryPlanner.scala:84)
at scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
at scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:157)
at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1336)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2.apply(QueryPlanner.scala:84)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2.apply(QueryPlanner.scala:76)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:102)
at org.apache.spark.sql.execution.SparkStrategies.plan(SparkStrategies.scala:76)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$sparkPlan$1.apply(QueryExecution.scala:99)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$sparkPlan$1.apply(QueryExecution.scala:95)
at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
at org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:95)
at org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:95)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$executedPlan$1.apply(QueryExecution.scala:106)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$executedPlan$1.apply(QueryExecution.scala:105)
at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:105)
at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:105)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withAction(Dataset.scala:3418)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2556)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2770)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:265)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:302)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:380)
at py4j.Gateway.invoke(Gateway.java:295)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:251)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.sql.SQLException: [Amazon](500310) Invalid operation: syntax error at or near ")"
Position: 5702;
at com.amazon.redshift.client.messages.inbound.ErrorResponse.toErrorException(Unknown Source)
at com.amazon.redshift.client.PGMessagingContext.handleErrorResponse(Unknown Source)
at com.amazon.redshift.client.PGMessagingContext.handleMessage(Unknown Source)
at com.amazon.jdbc.communications.InboundMessagesPipeline.getNextMessageOfClass(Unknown Source)
at com.amazon.redshift.client.PGMessagingContext.doMoveToNextClass(Unknown Source)
at com.amazon.redshift.client.PGMessagingContext.getErrorResponse(Unknown Source)
at com.amazon.redshift.client.PGClient.handleErrorsScenario2ForPrepareExecution(Unknown Source)
at com.amazon.redshift.client.PGClient.handleErrorsPrepareExecute(Unknown Source)
at com.amazon.redshift.client.PGClient.executePreparedStatement(Unknown Source)
at com.amazon.redshift.dataengine.PGQueryExecutor.executePreparedStatement(Unknown Source)
at com.amazon.redshift.dataengine.PGQueryExecutor.execute(Unknown Source)
at com.amazon.jdbc.common.SPreparedStatement.executeWithParams(Unknown Source)
at com.amazon.jdbc.common.SPreparedStatement.execute(Unknown Source)
at com.databricks.spark.redshift.JDBCWrapper$$anonfun$executeInterruptibly$1.apply(RedshiftJDBCWrapper.scala:187)
at com.databricks.spark.redshift.JDBCWrapper$$anonfun$executeInterruptibly$1.apply(RedshiftJDBCWrapper.scala:187)
at com.databricks.spark.redshift.JDBCWrapper$$anonfun$2.apply(RedshiftJDBCWrapper.scala:205)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
Caused by: com.amazon.support.exceptions.ErrorException: [Amazon](500310) Invalid operation: syntax error at or near ")"
Position: 5702;
... 20 more
Мой кластер Databricks имеет следующую среду выполнения
5.2 (includes Apache Spark 2.4.0, Scala 2.11)
и python 3, и я установил драйвер JDBC красного смещения RedshiftJDBC42_1_2_16_1027.jar.