[jira] [Created] (SPARK-39584) Fix TPCDSQueryBenchmark Measuring Performance of Wrong Query Results

["Kazuyuki Tanimura (Jira)" <ji...@apache.org>]

Kazuyuki Tanimura created SPARK-39584:
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             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



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