Hi ,
I want to load really large volumn datasets from mysql using spark dataframe
api. And then save as
parquet file or orc file to facilitate that with hive / Impala. The datasets
size is about 1 billion records and
when I am using the following naive code to run that , Error occurs and
executor lost failure.
val prop = new java.util.Properties
prop.setProperty("user","test")
prop.setProperty("password", "test")
val url1 = "jdbc:mysql://172.16.54.136:3306/db1"
val url2 = "jdbc:mysql://172.16.54.138:3306/db1"
val jdbcDF1 = sqlContext.read.jdbc(url1,"video",prop)
val jdbcDF2 = sqlContext.read.jdbc(url2,"video",prop)
val jdbcDF3 = jdbcDF1.unionAll(jdbcDF2)
jdbcDF3.write.format("parquet").save("hdfs://172.16.54.138:8020/perf")
I can see from the executor log and the message is like the following. I can
see from the log that the wait_timeout threshold reached
and there is no retry mechanism in the code process. So I am asking you experts
to help on tuning this. Or should I try to use a jdbc
connection pool to increase parallelism ?
16/01/19 17:04:28 ERROR executor.Executor: Exception in task 0.0 in stage
0.0 (TID 0)
com.mysql.jdbc.exceptions.jdbc4.CommunicationsException: Communications link
failure
The last packet successfully received from the server was 377,769 milliseconds
ago. The last packet sent successfully to the server was 377,790 milliseconds
ago.
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
Caused by: java.io.EOFException: Can not read response from server. Expected to
read 4 bytes, read 1 bytes before connection was unexpectedly lost.
at com.mysql.jdbc.MysqlIO.readFully(MysqlIO.java:2914)
at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:1996)
... 22 more
16/01/19 17:10:47 INFO executor.CoarseGrainedExecutorBackend: Got assigned task
4
16/01/19 17:10:47 INFO jdbc.JDBCRDD: closed connection
16/01/19 17:10:47 ERROR executor.Executor: Exception in task 1.1 in stage 0.0
(TID 2)
com.mysql.jdbc.exceptions.jdbc4.CommunicationsException: Communications link
failure
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