Hive can run into OOM (Out Of Memory) exceptions when writing many dynamic partitions to parquet because it creates too many open files at once and Parquet buffers an entire row group of data in memory for each open file. To avoid this in ORC,
HIVE-6455 shuffles data for each partition so only one file is open at a time. We need to extend this support to Parquet and possibly the MR and Spark planners.
Steps to reproduce:
1. Create a table and load some data that contains many many partitions (file data.txt attached on this ticket).
hive> create table t1_stage(id bigint, rdate string) row format delimited fields terminated by ' ';
hive> load data local inpath 'data.txt' into table t1_stage;
2. Create a Parquet table, and insert partitioned data from the t1_stage table.
hive> set hive.exec.dynamic.partition.mode=nonstrict;
hive> create table t1_part(id bigint) partitioned by (rdate string) stored as parquet;
hive> insert overwrite table t1_part partition(rdate) select * from t1_stage;
Query ID = sergio_20150330163713_db3afe74-d1c7-4f0d-a8f1-f2137ddb64a4
Total jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1427748520315_0006, Tracking URL = http://victory:8088/proxy/application_1427748520315_0006/
Kill Command = /opt/local/hadoop/bin/hadoop job -kill job_1427748520315_0006
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2015-03-30 16:37:19,065 Stage-1 map = 0%, reduce = 0%
2015-03-30 16:37:43,947 Stage-1 map = 100%, reduce = 0%
Ended Job = job_1427748520315_0006 with errors
Error during job, obtaining debugging information...
Examining task ID: task_1427748520315_0006_m_000000 (and more) from job job_1427748520315_0006
Task with the most failures(4):
Diagnostic Messages for this Task:
Error: Java heap space
FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask
MapReduce Jobs Launched:
Stage-Stage-1: Map: 1 HDFS Read: 0 HDFS Write: 0 FAIL
Total MapReduce CPU Time Spent: 0 msec