Dave DeCaprio created SPARK-26103:
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Summary: OutOfMemory error with large query plans
Key: SPARK-26103
URL: https://issues.apache.org/jira/browse/SPARK-26103
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.3.2, 2.3.1, 2.3.0
Environment: Amazon EMR 5.19
1 c5.4xlarge master instance
1 c5.4xlarge core instance
2 c5.4xlarge task instances
Reporter: Dave DeCaprio
Large query plans can cause OutOfMemory errors in the Spark driver.
We are creating data frames that are not extremely large but contain lots of
nested joins. These plans execute efficiently because of caching and
partitioning, but the text version of the query plans generated can be hundreds
of megabytes. Running many of these in parallel causes our driver process to
fail.
{{{{Exception in thread "main" java.lang.OutOfMemoryError: Java heap space at
java.util.Arrays.copyOfRange(Arrays.java:2694) at
java.lang.String.<init>(String.java:203) at
java.lang.StringBuilder.toString(StringBuilder.java:405) at
scala.StringContext.standardInterpolator(StringContext.scala:125) at
scala.StringContext.s(StringContext.scala:90) at
org.apache.spark.sql.execution.QueryExecution.toString(QueryExecution.scala:70)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:52)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:108)
}}}}
A similar error is reported in
[https://stackoverflow.com/questions/38307258/out-of-memory-error-when-writing-out-spark-dataframes-to-parquet-format]
Code exists to truncate the string if the number of output columns is larger
than 25, but not if the rest of the query plan is huge.
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