Kazuyuki Tanimura created SPARK-39584: -----------------------------------------
Summary: Fix TPCDSQueryBenchmark Measuring Performance of Wrong Query Results Key: SPARK-39584 URL: https://issues.apache.org/jira/browse/SPARK-39584 Project: Spark Issue Type: Test Components: Tests Affects Versions: 3.3.0, 3.2.1, 3.1.2, 3.0.3, 3.4.0 Reporter: Kazuyuki Tanimura GenTPCDSData uses the schema defined in `TPCDSSchema` that contains varchar(N)/char(N). When GenTPCDSData generates parquet, that pads spaces for strings whose lengths are < N. When TPCDSQueryBenchmark reads data from parquet generated by GenTPCDSData, it uses schema from the parquet file and keeps the paddings. Due to the extra spaces, string filter queries of TPC-DS fail to match. For example, q13 query results are all nulls and returns too fast because string filter does not meet any rows. Therefore, TPCDSQueryBenchmark is benchmarking with wrong query results and that is inflating some performance results. I am exploring two possible solutions now 1. Call `{{{}CREATE TABLE tableName schema USING parquet LOCATION path` {}}}before reading. This is what Spark unit tests are doing 2. Change varchar to string in the schema. This is what [databricks data generator| [https://github.com/databricks/spark-sql-perf]] is doing TPCDSQueryBenchmark was ported from databricks/spark-sql-perf in https://issues.apache.org/jira/browse/SPARK-35192 History related varchar https://lists.apache.org/thread/rg7pgwyto3616hb15q78n0sykls9j7rn -- This message was sent by Atlassian Jira (v8.20.7#820007) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org