# Spark SQL Performance Tests [![Build Status](https://travis-ci.org/databricks/spark-sql-perf.svg)](https://travis-ci.org/databricks/spark-sql-perf) This is a performance testing framework for [Spark SQL](https://spark.apache.org/sql/) in [Apache Spark](https://spark.apache.org/) 1.4+. **Note: This README is still under development. Please also check our source code for more information.** ## How to use it The rest of document will use TPC-DS benchmark as an example. We will add contents to explain how to use other benchmarks add the support of a new benchmark dataset in future. ### Setup a benchmark Before running any query, a dataset needs to be setup by creating a `Benchmark` object. ``` import com.databricks.spark.sql.perf.tpcds.Tables // Tables in TPC-DS benchmark used by experiments. // dsdgenDir is the location of dsdgen tool installed in your machines. val tables = new Tables(sqlContext, dsdgenDir, scaleFactor) // Generate data. tables.genData(location, format, overwrite, partitionTables, useDoubleForDecimal, clusterByPartitionColumns, filterOutNullPartitionValues) // Create metastore tables in a specified database for your data. // Once tables are created, the current database will be switched to the specified database. tables.createExternalTables(location, format, databaseName, overwrite) // Or, if you want to create temporary tables tables.createTemporaryTables(location, format) // Setup TPC-DS experiment import com.databricks.spark.sql.perf.tpcds.TPCDS val tpcds = new TPCDS (sqlContext = sqlContext) ``` ### Run benchmarking queries After setup, users can use `runExperiment` function to run benchmarking queries and record query execution time. Taking TPC-DS as an example, you can start an experiment by using ``` val experiment = tpcds.runExperiment(queriesToRun = tpcds.interactiveQueries) ``` For every experiment run (i.e. every call of `runExperiment`), Spark SQL Perf will use the timestamp of the start time to identify this experiment. Performance results will be stored in the sub-dir named by the timestamp in the given `resultsLocation` (for example `results/1429213883272`). The performance results are stored in the JSON format. ### Retrieve results While the experiment is running you can use `experiment.html` to list the status. Once the experiment is complete, the results will be saved to the table sqlPerformance in json. ``` // Get all experiments results. tpcds.createResultsTable() sqlContext.table("sqlPerformance") // Get the result of a particular run by specifying the timestamp of that run. sqlContext.table("sqlPerformance").filter("timestamp = 1429132621024") ```