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TPC-DS (2012)

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Similar to the Star Schema Benchmark (SSB), TPC-DS is based on TPC-H, but it took the opposite route, i.e. it expanded the number of joins needed by storing the data in a complex snowflake schema (24 instead of 8 tables). The data distribution is skewed (e.g. normal and Poisson distributions). It includes 99 reporting and ad-hoc queries with random substitutions.

References

Data Generation and Import

First, checkout the TPC-DS repository and compile the data generator:

git clone https://github.com/gregrahn/tpcds-kit.git
cd tpcds-kit/tools
make

Then, generate the data. Parameter -scale specifies the scale factor.

./dsdgen -scale 1

Now create tables in ClickHouse. The table definitions are available in init.sql in the ClickHouse repository.

The data can be imported as follows:

clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO call_center FORMAT CSV" < call_center.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO catalog_page FORMAT CSV" < catalog_page.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO catalog_returns FORMAT CSV" < catalog_returns.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO catalog_sales FORMAT CSV" < catalog_sales.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO customer FORMAT CSV" < customer.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO customer_address FORMAT CSV" < customer_address.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO customer_demographics FORMAT CSV" < customer_demographics.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO date_dim FORMAT CSV" < date_dim.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO household_demographics FORMAT CSV" < household_demographics.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO income_band FORMAT CSV" < income_band.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO inventory FORMAT CSV" < inventory.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO item FORMAT CSV" < item.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO promotion FORMAT CSV" < promotion.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO reason FORMAT CSV" < reason.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO ship_mode FORMAT CSV" < ship_mode.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO store FORMAT CSV" < store.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO store_returns FORMAT CSV" < store_returns.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO store_sales FORMAT CSV" < store_sales.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO time_dim FORMAT CSV" < time_dim.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO warehouse FORMAT CSV" < warehouse.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO web_page FORMAT CSV" < web_page.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO web_returns FORMAT CSV" < web_returns.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO web_sales FORMAT CSV" < web_sales.dat
clickhouse-client --format_csv_delimiter '|' --query "INSERT INTO web_site FORMAT CSV" < web_site.dat

Then run the generated queries.

Queries

The 99 TPC-DS queries can be found here in the ClickHouse repository.

To get SQL standard compatible behavior and expected results, apply the settings from settings.json. See the README for known issues and notes on specific queries.

Correctness

The results of the queries agree with the official results unless otherwise noted. There may be minor precision differences, which are permitted by the TPC-DS specification.

Performance benchmark

ClickHouse tracks TPC-DS query performance across every released version. You can explore run times for all 99 TPC-DS queries (scale factor 32) on the ClickHouse versions benchmark page to see how performance has evolved over time.

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