Benchmarks
Available Benchmarks and how to run them🔗
Benchmarks are located under <project-name>/jmh. It is generally favorable to only run the tests of interest rather than running all available benchmarks.
Also note that JMH benchmarks run within the same JVM as the system-under-test, so results might vary between runs.
Running Benchmarks on GitHub🔗
It is possible to run one or more Benchmarks via the JMH Benchmarks GH action on your own fork of the Iceberg repo. This GH action takes the following inputs:
* The repository name where those benchmarks should be run against, such as apache/iceberg or <user>/iceberg
* The branch name to run benchmarks against, such as main or my-cool-feature-branch
* A list of comma-separated double-quoted Benchmark names, such as "IcebergSourceFlatParquetDataReadBenchmark", "IcebergSourceFlatParquetDataFilterBenchmark", "IcebergSourceNestedListParquetDataWriteBenchmark"
Benchmark results will be uploaded once all benchmarks are done.
It is worth noting that the GH runners have limited resources so the benchmark results should rather be seen as an indicator to guide developers in understanding code changes. It is likely that there is variability in results across different runs, therefore the benchmark results shouldn't be used to form assumptions around production choices.
Running Benchmarks locally🔗
Below are the existing benchmarks shown with the actual commands on how to run them locally.
IcebergSourceNestedListParquetDataWriteBenchmark🔗
A benchmark that evaluates the performance of writing nested Parquet data using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceNestedListParquetDataWriteBenchmark -PjmhOutputPath=benchmark/iceberg-source-nested-list-parquet-data-write-benchmark-result.txt
SparkParquetReadersNestedDataBenchmark🔗
A benchmark that evaluates the performance of reading nested Parquet data using Iceberg and Spark Parquet readers. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=SparkParquetReadersNestedDataBenchmark -PjmhOutputPath=benchmark/spark-parquet-readers-nested-data-benchmark-result.txt
SparkParquetWritersFlatDataBenchmark🔗
A benchmark that evaluates the performance of writing Parquet data with a flat schema using Iceberg and Spark Parquet writers. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=SparkParquetWritersFlatDataBenchmark -PjmhOutputPath=benchmark/spark-parquet-writers-flat-data-benchmark-result.txt
IcebergSourceFlatORCDataReadBenchmark🔗
A benchmark that evaluates the performance of reading ORC data with a flat schema using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceFlatORCDataReadBenchmark -PjmhOutputPath=benchmark/iceberg-source-flat-orc-data-read-benchmark-result.txt
SparkParquetReadersFlatDataBenchmark🔗
A benchmark that evaluates the performance of reading Parquet data with a flat schema using Iceberg and Spark Parquet readers. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=SparkParquetReadersFlatDataBenchmark -PjmhOutputPath=benchmark/spark-parquet-readers-flat-data-benchmark-result.txt
VectorizedReadDictionaryEncodedFlatParquetDataBenchmark🔗
A benchmark to compare performance of reading Parquet dictionary encoded data with a flat schema using vectorized Iceberg read path and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=VectorizedReadDictionaryEncodedFlatParquetDataBenchmark -PjmhOutputPath=benchmark/vectorized-read-dict-encoded-flat-parquet-data-result.txt
IcebergSourceNestedListORCDataWriteBenchmark🔗
A benchmark that evaluates the performance of writing nested Parquet data using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceNestedListORCDataWriteBenchmark -PjmhOutputPath=benchmark/iceberg-source-nested-list-orc-data-write-benchmark-result.txt
VectorizedReadFlatParquetDataBenchmark🔗
A benchmark to compare performance of reading Parquet data with a flat schema using vectorized Iceberg read path and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=VectorizedReadFlatParquetDataBenchmark -PjmhOutputPath=benchmark/vectorized-read-flat-parquet-data-result.txt
IcebergSourceFlatParquetDataWriteBenchmark🔗
A benchmark that evaluates the performance of writing Parquet data with a flat schema using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceFlatParquetDataWriteBenchmark -PjmhOutputPath=benchmark/iceberg-source-flat-parquet-data-write-benchmark-result.txt
IcebergSourceNestedAvroDataReadBenchmark🔗
A benchmark that evaluates the performance of reading Avro data with a flat schema using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceNestedAvroDataReadBenchmark -PjmhOutputPath=benchmark/iceberg-source-nested-avro-data-read-benchmark-result.txt
IcebergSourceFlatAvroDataReadBenchmark🔗
A benchmark that evaluates the performance of reading Avro data with a flat schema using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceFlatAvroDataReadBenchmark -PjmhOutputPath=benchmark/iceberg-source-flat-avro-data-read-benchmark-result.txt
IcebergSourceNestedParquetDataWriteBenchmark🔗
A benchmark that evaluates the performance of writing nested Parquet data using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceNestedParquetDataWriteBenchmark -PjmhOutputPath=benchmark/iceberg-source-nested-parquet-data-write-benchmark-result.txt
IcebergSourceNestedParquetDataReadBenchmark🔗
- A benchmark that evaluates the performance of reading nested Parquet data using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceNestedParquetDataReadBenchmark -PjmhOutputPath=benchmark/iceberg-source-nested-parquet-data-read-benchmark-result.txt
IcebergSourceNestedORCDataReadBenchmark🔗
A benchmark that evaluates the performance of reading ORC data with a flat schema using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceNestedORCDataReadBenchmark -PjmhOutputPath=benchmark/iceberg-source-nested-orc-data-read-benchmark-result.txt
IcebergSourceFlatParquetDataReadBenchmark🔗
A benchmark that evaluates the performance of reading Parquet data with a flat schema using Iceberg and the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceFlatParquetDataReadBenchmark -PjmhOutputPath=benchmark/iceberg-source-flat-parquet-data-read-benchmark-result.txt
IcebergSourceFlatParquetDataFilterBenchmark🔗
A benchmark that evaluates the file skipping capabilities in the Spark data source for Iceberg. This class uses a dataset with a flat schema, where the records are clustered according to the column used in the filter predicate. The performance is compared to the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceFlatParquetDataFilterBenchmark -PjmhOutputPath=benchmark/iceberg-source-flat-parquet-data-filter-benchmark-result.txt
IcebergSourceNestedParquetDataFilterBenchmark🔗
A benchmark that evaluates the file skipping capabilities in the Spark data source for Iceberg. This class uses a dataset with nested data, where the records are clustered according to the
column used in the filter predicate. The performance is compared to the built-in file source in Spark. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=IcebergSourceNestedParquetDataFilterBenchmark -PjmhOutputPath=benchmark/iceberg-source-nested-parquet-data-filter-benchmark-result.txt
SparkParquetWritersNestedDataBenchmark🔗
- A benchmark that evaluates the performance of writing nested Parquet data using Iceberg and Spark Parquet writers. To run this benchmark for either spark-2 or spark-3:
./gradlew :iceberg-spark:iceberg-spark[2|3]:jmh -PjmhIncludeRegex=SparkParquetWritersNestedDataBenchmark -PjmhOutputPath=benchmark/spark-parquet-writers-nested-data-benchmark-result.txt