Writing to SQL Database - ConnectionException - PySpark
I'm attempting to write a dataframe to OmniSci's database, basically a GPU-backed SQL database. I'm receiving a strange error when attempting to do so:
subs_dim.write.format("jdbc").option("url", "jdbc:mapd:EC2ADDRESS.compute-1.amazonaws.com:9091:mapd").option("driver", "com.mapd.jdbc.MapDDriver").option("dbtable", "subs_dim").option("user", "mapd").option("password", "INSTANCEID").save()
and receiving this error:
java.sql.SQLException: Connection failed - org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection timed out (Connection timed out)
Py4JJavaError: An error occurred while calling o309.save.
: java.sql.SQLException: Connection failed - org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection timed out (Connection timed out)
at com.mapd.jdbc.MapDConnection.(MapDConnection.java:113)
at com.mapd.jdbc.MapDDriver.connect(MapDDriver.java:55)
at org.apache.spark.sql.execution.datasources.jdbc.DriverWrapper.connect(DriverWrapper.scala:45)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:63)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:54)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:63)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:72)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:88)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:150)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:138)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$5.apply(SparkPlan.scala:190)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:187)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:138)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:108)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:108)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:683)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:683)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1.apply(SQLExecution.scala:89)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:175)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:84)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:126)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:683)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:287)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:281)
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)
Anyone have ideas? I've pinged the server and confirmed that port is open
database apache-spark pyspark thrift spark-thriftserver
asked Nov 21 '18 at 16:11
DataScienceAmateurDataScienceAmateur
71128
add a comment |
I'm attempting to write a dataframe to OmniSci's database, basically a GPU-backed SQL database. I'm receiving a strange error when attempting to do so:
subs_dim.write.format("jdbc").option("url", "jdbc:mapd:EC2ADDRESS.compute-1.amazonaws.com:9091:mapd").option("driver", "com.mapd.jdbc.MapDDriver").option("dbtable", "subs_dim").option("user", "mapd").option("password", "INSTANCEID").save()
and receiving this error:
java.sql.SQLException: Connection failed - org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection timed out (Connection timed out)
Py4JJavaError: An error occurred while calling o309.save.
: java.sql.SQLException: Connection failed - org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection timed out (Connection timed out)
at com.mapd.jdbc.MapDConnection.(MapDConnection.java:113)
at com.mapd.jdbc.MapDDriver.connect(MapDDriver.java:55)
at org.apache.spark.sql.execution.datasources.jdbc.DriverWrapper.connect(DriverWrapper.scala:45)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:63)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:54)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:63)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:72)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:88)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:150)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:138)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$5.apply(SparkPlan.scala:190)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:187)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:138)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:108)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:108)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:683)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:683)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1.apply(SQLExecution.scala:89)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:175)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:84)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:126)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:683)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:287)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:281)
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)
Anyone have ideas? I've pinged the server and confirmed that port is open
database apache-spark pyspark thrift spark-thriftserver
asked Nov 21 '18 at 16:11
DataScienceAmateurDataScienceAmateur
71128
Maybe, exception occurs on executor node, where server is not visible.
– pasha701
Nov 21 '18 at 16:28
Hmm interesting theory. How would I go about rectifying that?
– DataScienceAmateur
Nov 21 '18 at 16:55
Executor computer (IP address) where error occurs, can be found with Spark History server, or in other way. Then try to connect to server from this computer for confirm cause.
– pasha701
Nov 21 '18 at 16:58
add a comment |
I'm attempting to write a dataframe to OmniSci's database, basically a GPU-backed SQL database. I'm receiving a strange error when attempting to do so:
subs_dim.write.format("jdbc").option("url", "jdbc:mapd:EC2ADDRESS.compute-1.amazonaws.com:9091:mapd").option("driver", "com.mapd.jdbc.MapDDriver").option("dbtable", "subs_dim").option("user", "mapd").option("password", "INSTANCEID").save()
and receiving this error:
java.sql.SQLException: Connection failed - org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection timed out (Connection timed out)
Py4JJavaError: An error occurred while calling o309.save.
: java.sql.SQLException: Connection failed - org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection timed out (Connection timed out)
at com.mapd.jdbc.MapDConnection.(MapDConnection.java:113)
at com.mapd.jdbc.MapDDriver.connect(MapDDriver.java:55)
at org.apache.spark.sql.execution.datasources.jdbc.DriverWrapper.connect(DriverWrapper.scala:45)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:63)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:54)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:63)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:72)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:88)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:150)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:138)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$5.apply(SparkPlan.scala:190)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:187)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:138)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:108)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:108)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:683)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:683)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1.apply(SQLExecution.scala:89)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:175)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:84)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:126)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:683)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:287)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:281)
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)
Anyone have ideas? I've pinged the server and confirmed that port is open
database apache-spark pyspark thrift spark-thriftserver
asked Nov 21 '18 at 16:11
DataScienceAmateurDataScienceAmateur
71128
I'm attempting to write a dataframe to OmniSci's database, basically a GPU-backed SQL database. I'm receiving a strange error when attempting to do so:
subs_dim.write.format("jdbc").option("url", "jdbc:mapd:EC2ADDRESS.compute-1.amazonaws.com:9091:mapd").option("driver", "com.mapd.jdbc.MapDDriver").option("dbtable", "subs_dim").option("user", "mapd").option("password", "INSTANCEID").save()
and receiving this error:
java.sql.SQLException: Connection failed - org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection timed out (Connection timed out)
Py4JJavaError: An error occurred while calling o309.save.
: java.sql.SQLException: Connection failed - org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection timed out (Connection timed out)
at com.mapd.jdbc.MapDConnection.(MapDConnection.java:113)
at com.mapd.jdbc.MapDDriver.connect(MapDDriver.java:55)
at org.apache.spark.sql.execution.datasources.jdbc.DriverWrapper.connect(DriverWrapper.scala:45)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:63)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:54)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:63)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:72)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:88)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:150)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:138)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$5.apply(SparkPlan.scala:190)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:187)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:138)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:108)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:108)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:683)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:683)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1.apply(SQLExecution.scala:89)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:175)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:84)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:126)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:683)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:287)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:281)
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)
Anyone have ideas? I've pinged the server and confirmed that port is open
database apache-spark pyspark thrift spark-thriftserver
database apache-spark pyspark thrift spark-thriftserver
asked Nov 21 '18 at 16:11
DataScienceAmateurDataScienceAmateur
71128
asked Nov 21 '18 at 16:11
DataScienceAmateurDataScienceAmateur
71128
asked Nov 21 '18 at 16:11
DataScienceAmateurDataScienceAmateur
71128
asked Nov 21 '18 at 16:11
DataScienceAmateurDataScienceAmateur
71128
asked Nov 21 '18 at 16:11
DataScienceAmateurDataScienceAmateur
71128
71128
Maybe, exception occurs on executor node, where server is not visible.
– pasha701
Nov 21 '18 at 16:28
Hmm interesting theory. How would I go about rectifying that?
– DataScienceAmateur
Nov 21 '18 at 16:55
Executor computer (IP address) where error occurs, can be found with Spark History server, or in other way. Then try to connect to server from this computer for confirm cause.
– pasha701
Nov 21 '18 at 16:58
add a comment |
Maybe, exception occurs on executor node, where server is not visible.
– pasha701
Nov 21 '18 at 16:28
Hmm interesting theory. How would I go about rectifying that?
– DataScienceAmateur
Nov 21 '18 at 16:55
Executor computer (IP address) where error occurs, can be found with Spark History server, or in other way. Then try to connect to server from this computer for confirm cause.
– pasha701
Nov 21 '18 at 16:58
Maybe, exception occurs on executor node, where server is not visible.
– pasha701
Nov 21 '18 at 16:28
Maybe, exception occurs on executor node, where server is not visible.
– pasha701
Nov 21 '18 at 16:28
Hmm interesting theory. How would I go about rectifying that?
– DataScienceAmateur
Nov 21 '18 at 16:55
Hmm interesting theory. How would I go about rectifying that?
– DataScienceAmateur
Nov 21 '18 at 16:55
Executor computer (IP address) where error occurs, can be found with Spark History server, or in other way. Then try to connect to server from this computer for confirm cause.
– pasha701
Nov 21 '18 at 16:58
Executor computer (IP address) where error occurs, can be found with Spark History server, or in other way. Then try to connect to server from this computer for confirm cause.
– pasha701
Nov 21 '18 at 16:58
add a comment |
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Maybe, exception occurs on executor node, where server is not visible.
– pasha701
Nov 21 '18 at 16:28
Hmm interesting theory. How would I go about rectifying that?
– DataScienceAmateur
Nov 21 '18 at 16:55
Executor computer (IP address) where error occurs, can be found with Spark History server, or in other way. Then try to connect to server from this computer for confirm cause.
– pasha701
Nov 21 '18 at 16:58