This are set of UDFs and queries that you can use with Hive to use TPCH datagen in parrellel on hadoop cluster. You can deploy to azure using :

1. Clone this repo.

   git clone https://github.com/dharmeshkakadia/tpch-datagen-as-hive-query/ && cd tpch-datagen-as-hive-query

2. Run TPCHDataGen.hql with settings.hql file and set the required config variables.

   hive -i settings.hql -f TPCHDataGen.hql -hiveconf SCALE=10 -hiveconf PARTS=10 -hiveconf LOCATION=/HiveTPCH/ -hiveconf TPCHBIN=resources 

   Here, SCALE is a scale factor for TPCH, PARTS is a number of task to use for datagen (parrellelization), LOCATION is the directory where the data will be stored on HDFS, TPCHBIN is where the resources are found. You can specify specific settings in settings.hql file.

3. Now you can create tables on the generated data.

   hive -i settings.hql -f ddl/createAllExternalTables.hql -hiveconf LOCATION=/HiveTPCH/ -hiveconf DBNAME=tpch

   Generate ORC tables and analyze

   hive -i settings.hql -f ddl/createAllORCTables.hql -hiveconf ORCDBNAME=tpch_orc -hiveconf SOURCE=tpch 
   hive -i settings.hql -f ddl/analyze.hql -hiveconf ORCDBNAME=tpch_orc 

4. Run the queries !

   hive -database tpch_orc -i settings.hql -f queries/tpch_query1.hql 

1. Clone this repo.

   git clone https://github.com/dharmeshkakadia/tpch-datagen-as-hive-query/ && cd tpch-datagen-as-hive-query

2. Upload the resources to DFS.

   hdfs dfs -copyFromLocal resoruces /tmp

3. Run TPCHDataGen.hql with settings.hql file and set the required config variables.

   beeline -u "jdbc:hive2://`hostname -f`:10001/;transportMode=http" -n "" -p "" -i settings.hql -f TPCHDataGen.hql -hiveconf SCALE=10 -hiveconf PARTS=10 -hiveconf LOCATION=/HiveTPCH/ -hiveconf TPCHBIN=`grep -A 1 "fs.defaultFS" /etc/hadoop/conf/core-site.xml | grep -o "wasb[^<]*"`/tmp/resources 

   Here, SCALE is a scale factor for TPCH, PARTS is a number of task to use for datagen (parrellelization), LOCATION is the directory where the data will be stored on HDFS, TPCHBIN is where the resources are uploaded on step 2. You can specify specific settings in settings.hql file.

4. Now you can create tables on the generated data.

   beeline -u "jdbc:hive2://`hostname -f`:10001/;transportMode=http" -n "" -p "" -i settings.hql -f ddl/createAllExternalTables.hql -hiveconf LOCATION=/HiveTPCH/ -hiveconf DBNAME=tpch

   Generate ORC tables and analyze

   beeline -u "jdbc:hive2://`hostname -f`:10001/;transportMode=http" -n "" -p "" -i settings.hql -f ddl/createAllORCTables.hql -hiveconf ORCDBNAME=tpch_orc -hiveconf SOURCE=tpch 
   beeline -u "jdbc:hive2://`hostname -f`:10001/;transportMode=http" -n "" -p "" -i settings.hql -f ddl/analyze.hql -hiveconf ORCDBNAME=tpch_orc 

5. Run the queries !

   beeline -u "jdbc:hive2://`hostname -f`:10001/tpch_orc;transportMode=http" -n "" -p "" -i settings.hql -f queries/tpch_query1.hql 

If you want to run all the queries 10 times and measure the times it takes, you can use the following command:

for f in queries/*.sql; do for i in {1..10} ; do STARTTIME="`date +%s`";  beeline -u "jdbc:hive2://`hostname -f`:10001/tpch_orc;transportMode=http" -i settings.hql -f $f  > $f.run_$i.out 2>&1 ; ENDTIME="`date +%s`"; echo "$f,$i,$STARTTIME,$ENDTIME,$(($ENDTIME-$STARTTIME))" >> times_orc.csv; done; done;

1. Does it work with scale factor 1?

   No. The parrellel data generation assumes that scale > 1. If you are just starting out, I would suggest you start with 10 and then move to standard higher scale factors (100, 1000, 10000,..)

2. Do I have to specify PARTS=SCALE ?

   Yes.

3. How do I avoid my session getting killed due to network errors while long running benchmark?

   Use byobu. Type byobu which will start a new session and then run the command. It will be there when you come back even if your network connection is broken.