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spark-instrumented-optimizer/sql/core/benchmarks/JsonBenchmark-results.txt

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[SPARK-25847][SQL][TEST] Refactor JSONBenchmarks to use main method ## What changes were proposed in this pull request? Refactor JSONBenchmark to use main method use spark-submit: `bin/spark-submit --class org.apache.spark.sql.execution.datasources.json.JSONBenchmark --jars ./core/target/spark-core_2.11-3.0.0-SNAPSHOT-tests.jar,./sql/catalyst/target/spark-catalyst_2.11-3.0.0-SNAPSHOT-tests.jar ./sql/core/target/spark-sql_2.11-3.0.0-SNAPSHOT-tests.jar` Generate benchmark result: `SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/test:runMain org.apache.spark.sql.execution.datasources.json.JSONBenchmark"` ## How was this patch tested? manual tests Closes #22844 from heary-cao/JSONBenchmarks. Lead-authored-by: caoxuewen <cao.xuewen@zte.com.cn> Co-authored-by: heary <cao.xuewen@zte.com.cn> Co-authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: hyukjinkwon <gurwls223@apache.org>
2018-10-30 22:28:17 -04:00
================================================================================================
Benchmark for performance of JSON parsing
================================================================================================
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
JSON schema inferring: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
No encoding 63981 64044 56 1.6 639.8 1.0X
UTF-8 is set 112672 113350 962 0.9 1126.7 0.6X
[SPARK-25847][SQL][TEST] Refactor JSONBenchmarks to use main method ## What changes were proposed in this pull request? Refactor JSONBenchmark to use main method use spark-submit: `bin/spark-submit --class org.apache.spark.sql.execution.datasources.json.JSONBenchmark --jars ./core/target/spark-core_2.11-3.0.0-SNAPSHOT-tests.jar,./sql/catalyst/target/spark-catalyst_2.11-3.0.0-SNAPSHOT-tests.jar ./sql/core/target/spark-sql_2.11-3.0.0-SNAPSHOT-tests.jar` Generate benchmark result: `SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/test:runMain org.apache.spark.sql.execution.datasources.json.JSONBenchmark"` ## How was this patch tested? manual tests Closes #22844 from heary-cao/JSONBenchmarks. Lead-authored-by: caoxuewen <cao.xuewen@zte.com.cn> Co-authored-by: heary <cao.xuewen@zte.com.cn> Co-authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: hyukjinkwon <gurwls223@apache.org>
2018-10-30 22:28:17 -04:00
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
count a short column: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
No encoding 51256 51449 180 2.0 512.6 1.0X
UTF-8 is set 83694 83859 148 1.2 836.9 0.6X
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
count a wide column: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
No encoding 58440 59097 569 0.2 5844.0 1.0X
UTF-8 is set 102746 102883 198 0.1 10274.6 0.6X
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
select wide row: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
No encoding 128982 129304 356 0.0 257965.0 1.0X
UTF-8 is set 147247 147415 231 0.0 294494.1 0.9X
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Select a subset of 10 columns: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
Select 10 columns 18837 19048 331 0.5 1883.7 1.0X
Select 1 column 24707 24723 14 0.4 2470.7 0.8X
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
creation of JSON parser per line: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
Short column without encoding 8218 8234 17 1.2 821.8 1.0X
Short column with UTF-8 12374 12438 107 0.8 1237.4 0.7X
Wide column without encoding 136918 137298 345 0.1 13691.8 0.1X
Wide column with UTF-8 176961 177142 257 0.1 17696.1 0.0X
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
JSON functions: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
Text read 1268 1278 12 7.9 126.8 1.0X
from_json 23348 23479 176 0.4 2334.8 0.1X
json_tuple 29606 30221 1024 0.3 2960.6 0.0X
get_json_object 21898 22148 226 0.5 2189.8 0.1X
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Dataset of json strings: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
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[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
Text read 5887 5944 49 8.5 117.7 1.0X
schema inferring 46696 47054 312 1.1 933.9 0.1X
parsing 32336 32450 129 1.5 646.7 0.2X
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Preparing data for benchmarking ...
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27327][SQL] New JSON benchmarks: functions, Dataset[String] ## What changes were proposed in this pull request? Added new benchmarks for: 1. JSON functions: `from_json`, `json_tuple` and `get_json_object` 2. Parsing `Dataset[String]` with JSON records 3. Comparing just splitting input text by lines with schema inferring, per-line parsing when encoding is set and not set. Also existing benchmarks were refactored to use the `NoOp` datasource to eliminate overhead of triggers like `.filter((_: Row) => true).count()`. ## How was this patch tested? By running `JSONBenchmark` locally. Closes #24252 from MaxGekk/json-benchmark-func. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-31 19:33:16 -04:00
Json files in the per-line mode: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
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[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
Text read 9756 9769 11 5.1 195.1 1.0X
Schema inferring 51318 51433 108 1.0 1026.4 0.2X
Parsing without charset 43609 43743 118 1.1 872.2 0.2X
Parsing with UTF-8 60775 60844 106 0.8 1215.5 0.2X
[SPARK-27535][SQL][TEST] Date and timestamp JSON benchmarks ## What changes were proposed in this pull request? Added new JSON benchmarks related to date and timestamps operations: - Write date/timestamp to JSON files - `to_json()` and `from_json()` for dates and timestamps - Read date/timestamps from JSON files, and infer schemas - Parse and infer schemas from `Dataset[String]` Also existing JSON benchmarks are ported on `NoOp` datasource. Closes #24430 from MaxGekk/json-datetime-benchmark. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-04-22 22:09:14 -04:00
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27535][SQL][TEST] Date and timestamp JSON benchmarks ## What changes were proposed in this pull request? Added new JSON benchmarks related to date and timestamps operations: - Write date/timestamp to JSON files - `to_json()` and `from_json()` for dates and timestamps - Read date/timestamps from JSON files, and infer schemas - Parse and infer schemas from `Dataset[String]` Also existing JSON benchmarks are ported on `NoOp` datasource. Closes #24430 from MaxGekk/json-datetime-benchmark. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-04-22 22:09:14 -04:00
Write dates and timestamps: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
Create a dataset of timestamps 1998 2015 17 5.0 199.8 1.0X
to_json(timestamp) 18156 18317 263 0.6 1815.6 0.1X
write timestamps to files 12912 12917 5 0.8 1291.2 0.2X
Create a dataset of dates 2209 2270 53 4.5 220.9 0.9X
to_json(date) 9433 9489 90 1.1 943.3 0.2X
write dates to files 6915 6923 8 1.4 691.5 0.3X
[SPARK-27535][SQL][TEST] Date and timestamp JSON benchmarks ## What changes were proposed in this pull request? Added new JSON benchmarks related to date and timestamps operations: - Write date/timestamp to JSON files - `to_json()` and `from_json()` for dates and timestamps - Read date/timestamps from JSON files, and infer schemas - Parse and infer schemas from `Dataset[String]` Also existing JSON benchmarks are ported on `NoOp` datasource. Closes #24430 from MaxGekk/json-datetime-benchmark. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-04-22 22:09:14 -04:00
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
[SPARK-27535][SQL][TEST] Date and timestamp JSON benchmarks ## What changes were proposed in this pull request? Added new JSON benchmarks related to date and timestamps operations: - Write date/timestamp to JSON files - `to_json()` and `from_json()` for dates and timestamps - Read date/timestamps from JSON files, and infer schemas - Parse and infer schemas from `Dataset[String]` Also existing JSON benchmarks are ported on `NoOp` datasource. Closes #24430 from MaxGekk/json-datetime-benchmark. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-04-22 22:09:14 -04:00
Read dates and timestamps: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[SPARK-31755][SQL][FOLLOWUP] Update date-time, CSV and JSON benchmark results ### What changes were proposed in this pull request? Re-generate results of: - DateTimeBenchmark - CSVBenchmark - JsonBenchmark in the environment: | Item | Description | | ---- | ----| | Region | us-west-2 (Oregon) | | Instance | r3.xlarge | | AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) | | Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 | ### Why are the changes needed? 1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing. 2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running benchmarks via the script: ```python #!/usr/bin/env python3 import os from sparktestsupport.shellutils import run_cmd benchmarks = [ ['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'], ['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark'] ] print('Set SPARK_GENERATE_BENCHMARK_FILES=1') os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1' for b in benchmarks: print("Run benchmark: %s" % b[1]) run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])]) ``` Closes #28613 from MaxGekk/missing-hour-year-benchmarks. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-25 11:00:11 -04:00
read timestamp text from files 2395 2412 17 4.2 239.5 1.0X
read timestamps from files 47269 47334 89 0.2 4726.9 0.1X
infer timestamps from files 91806 91851 67 0.1 9180.6 0.0X
read date text from files 2118 2133 13 4.7 211.8 1.1X
read date from files 17267 17340 115 0.6 1726.7 0.1X
timestamp strings 3906 3935 26 2.6 390.6 0.6X
parse timestamps from Dataset[String] 52244 52534 279 0.2 5224.4 0.0X
infer timestamps from Dataset[String] 100488 100714 198 0.1 10048.8 0.0X
date strings 4572 4584 12 2.2 457.2 0.5X
parse dates from Dataset[String] 26749 26768 17 0.4 2674.9 0.1X
from_json(timestamp) 71414 71867 556 0.1 7141.4 0.0X
from_json(date) 45322 45549 250 0.2 4532.2 0.1X
[SPARK-27535][SQL][TEST] Date and timestamp JSON benchmarks ## What changes were proposed in this pull request? Added new JSON benchmarks related to date and timestamps operations: - Write date/timestamp to JSON files - `to_json()` and `from_json()` for dates and timestamps - Read date/timestamps from JSON files, and infer schemas - Parse and infer schemas from `Dataset[String]` Also existing JSON benchmarks are ported on `NoOp` datasource. Closes #24430 from MaxGekk/json-datetime-benchmark. Authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-04-22 22:09:14 -04:00
[SPARK-25847][SQL][TEST] Refactor JSONBenchmarks to use main method ## What changes were proposed in this pull request? Refactor JSONBenchmark to use main method use spark-submit: `bin/spark-submit --class org.apache.spark.sql.execution.datasources.json.JSONBenchmark --jars ./core/target/spark-core_2.11-3.0.0-SNAPSHOT-tests.jar,./sql/catalyst/target/spark-catalyst_2.11-3.0.0-SNAPSHOT-tests.jar ./sql/core/target/spark-sql_2.11-3.0.0-SNAPSHOT-tests.jar` Generate benchmark result: `SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/test:runMain org.apache.spark.sql.execution.datasources.json.JSONBenchmark"` ## How was this patch tested? manual tests Closes #22844 from heary-cao/JSONBenchmarks. Lead-authored-by: caoxuewen <cao.xuewen@zte.com.cn> Co-authored-by: heary <cao.xuewen@zte.com.cn> Co-authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: hyukjinkwon <gurwls223@apache.org>
2018-10-30 22:28:17 -04:00
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