Based on TPC-DS v1.1.0 found at http://www.tpc.org/tpcds/ and the Cloudera Impala benchmark

NOTICE: This repo contains modifications to the official TPC-DS specification so any results from this are not comparable to officially audited results.

The following tables are currently used:

Dimension Tables:

• DATE_DIM
• TIME_DIM
• CUSTOMER
• CUSTOMER_ADDRESS
• CUSTOMER_DEMOGRAPHICS
• HOUSEHOLD_DEMOGRAPHICS
• ITEM
• PROMOTION
• STORE

Fact Tables:

• STORE_SALES

These steps setup your environment to perform a distributed data generation for the given scale factor.

The scripts assume that you have passwordless SSH from the master node (where you will clone the repos to) to every DataNode that is in your cluster.

• cd $HOME
• clone this repo git clone https://github.com/sohan/vertica-tpcds-kit
• cd vertica-tpcds-kit
• cp tpcds-env-sample.sh tpcds-env.sh and modify tpcds-env.sh as needed.
• Edit dn.txt and put one DataNode hostname per line - no blank lines.
• Run push-bits.sh which will scp vertica-tpcds-kit and build tpcds-kit on each DataNode listed in dn.txt.
• Run set-nodenum.sh. This will create vertica-tpcds-kit/nodenum.sh on every DataNode and set the value accordingly. This is used to determine what portion of the distributed data generation is done on each node.

Data is landed directly in Vertica so there is no requirement for any local storage. Run the following in order:

• pip install -r requirements.txt - Download python dependencies (recommended: use virtualenv)
• vertica-create-tables.sh - Creates tables in Vertica
• run-gen-dims.sh - Runs gen-dims.sh on the first node in dn.txt. Generate dimension data and insert into Vertica
• run-gen-facts.sh - Runs gen-facts.sh on each DataNode via ssh to generate the store_sales table.

You can run queries in a single-user or multi-user (concurrent) setting. See below for usage.

./vertica-run-queries.sh --help
# single user run. queries are shuffled and then run sequentially:
./vertica-run-queries.sh --interactive --num-users 1 --num-runs 3

# multi-user run. for each run, asynchronously for each user, queries shuffled and run sequentially.
./vertica-run-queries.sh --interactive --num-users 5 --num-runs 3

cat results/*-scale-5-users-3-runs/metadata.json

{
    "metadata": {
        "num_users": 5, 
        "num_runs": 3, 
        "start_time": "2014-09-04 15:50:38.380715", 
        "scale_factor": "10", 
        "queries": [
            "q19", 
            ...
        ]
    }
}

cat results/*-scale-5-users-3-runs/query_times.csv

"run_number","user","query","time_s"
"1","1","q42","0.17443999999999998"
"1","1","q52","0.432267"
"1","2","q19","0.763254"
"1","3","q52","0.467401"
"1","2","q42","0.509011"
"1","3","q42","0.760072"
"1","1","q19","1.065039"
"1","3","q73","0.469087"
"1","4","q68","1.527678"
"1","1","q98","1.8634000000000002"
"1","4","q98","2.42102"
"1","5","q98","2.111182"
...