Hello,
Spark sql is generating query plan with all partitions information even
though if we apply filters on partitions in the query. Due to this, spark
driver/hive metastore is hitting with OOM as each table is with lots of
partitions.
We can confirm from hive audit logs that it tries to *fetch all partitions*
from hive metastore.
2016-12-28 07:18:33,749 INFO [pool-4-thread-184]: HiveMetaStore.audit
(HiveMetaStore.java:logAuditEvent(371)) - ugi=rajub ip=/x.x.x.x
cmd=get_partitions : db=xxxx tbl=xxxxx
Configured the following parameters in the spark conf to fix the above
issue(source: from spark-jira & github pullreq):
*spark.sql.hive.convertMetastoreParquet false*
* spark.sql.hive.metastorePartitionPruning true*
* plan: rdf.explain*
* == Physical Plan ==*
HiveTableScan [rejection_reason#626], MetastoreRelation dbname,
tablename, None, [(year#314 = 2016),(month#315 = 12),(day#316 =
28),(hour#317 = 2),(venture#318 = DEFAULT)]
* get_partitions_by_filter* method is called and fetching only required
partitions.
But we are seeing parquetDecode errors in our applications frequently
after this. Looks like these decoding errors were because of changing
serde from spark-builtin to hive serde.
I feel like,* fixing query plan generation in the spark-sql* is the right
approach instead of forcing users to use hive serde.
Is there any workaround/way to fix this issue? I would like to hear more
thoughts on this :)
------
Thanks,
Raju Bairishetti,
www.lazada.com
