hive query performance is bad

Question

I am joining 3 huge tables (billion row tables) in HIVE. All the statistics are collected, but still the performance is very bad (query taking 40 minutes odd).

Is there any parameter which I can set in the HIVE prompt to get better performance?

When I am trying execution I am seeing info like

Sep 4, 2015 7:40:23 AM INFO: parquet.hadoop.ParquetInputFormat: Total input paths to process : 1
Sep 4, 2015 7:40:23 AM INFO: parquet.hadoop.ParquetFileReader: reading another 1 footers

All the tables are created in BigSql with storage parameter as "STORED AS PARQUETFILE"

How can I suppress the job progress details when a HIVE query is running?

Regarding HIVE version

 hive> set system:sun.java.command; system:sun.java.command=org.apache.hadoop.util.RunJar /opt/ibm/biginsights/hive/lib/hive-cli-0.12.0.jar org.apache.hadoop.hive.cli.CliDriver -hiveconf hive.aux.jars.path=file:///opt/ibm/biginsights/hive/lib/hive-hbase-handler-0.12.0.jar,file:///opt/ibm/biginsights/hive/lib/hive-contrib-0.12.0.jar,file:///opt/ibm/biginsights/hive/lib/hbase-client-0.96.0.jar,file:///opt/ibm/biginsights/hive/lib/hbase-common-0.96.0.jar,file:///opt/ibm/biginsights/hive/lib/hbase-hadoop2-compat-0.96.0.jar,file:///opt/ibm/biginsights/hive/lib/hbase-prefix-tree-0.96.0.jar,file:///opt/ibm/biginsights/hive/lib/hbase-protocol-0.96.0.jar,file:///opt/ibm/biginsights/hive/lib/hbase-server-0.96.0.jar,file:///opt/ibm/biginsights/hive/lib/htrace-core-2.01.jar,file:///opt/ibm/biginsights/hive/lib/zookeeper-3.4.5.jar,file:///opt/ibm/biginsights/sheets/libext/piggybank.jar,file:///opt/ibm/biginsights/sheets/libext/pig-0.11.1.jar,file:///opt/ibm/biginsights/sheets/libext/avro-1.7.4.jar,file:///opt/ibm/biginsights/sheets/libext/opencsv-1.8.jar,file:///opt/ibm/biginsights/sheets/libext/json-simple-1.1.jar,file:///opt/ibm/biginsights/sheets/libext/joda-time-1.6.jar,file:///opt/ibm/biginsights/sheets/libext/bigsheets.jar,file:///opt/ibm/biginsights/sheets/libext/bigsheets-serdes-1.0.0.jar,file:///opt/ibm/biginsights/lib/parquet/parquet-mr/parquet-column-1.3.2.jar,file:///opt/ibm/biginsights/lib/parquet/parquet-mr/parquet-common-1.3.2.jar,file:///opt/ibm/biginsights/lib/parquet/parquet-mr/parquet-encoding-1.3.2.jar,file:///opt/ibm/biginsights/lib/parquet/parquet-mr/parquet-generator-1.3.2.jar,file:///opt/ibm/biginsights/lib/parquet/parquet-mr/parquet-hadoop-bundle-1.3.2.jar,file:///opt/ibm/biginsights/lib/parquet/parquet-mr/parquet-hive-bundle-1.3.2.jar,file:///opt/ibm/biginsights/lib/parquet/parquet-mr/parquet-thrift-1.3.2.jar,file:///opt/ibm/biginsights/hive/lib/guava-11.0.2.jar 

Answer 1

Koushik - This question I asked a month back will give you a good insight to performance of ORC vs Parquet.

Let me ask this question! What is the structure of your data? Is this nested or flatter? If this is a flatter data, example can be data ingested from an RDBMS, ORC is better since it has light indexes stored alongside the data and makes data retrieval faster.

Hope this helps