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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-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
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
JSON schema inferring: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
No encoding 50949 51086 150 2.0 509.5 1.0X
UTF-8 is set 72012 72147 120 1.4 720.1 0.7X
[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 ...
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
count a short column: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
No encoding 36799 36891 80 2.7 368.0 1.0X
UTF-8 is set 59796 59880 74 1.7 598.0 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 ...
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
count a wide column: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
No encoding 55803 55967 152 0.2 5580.3 1.0X
UTF-8 is set 80623 80825 178 0.1 8062.3 0.7X
[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 ...
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
select wide row: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
No encoding 84263 85750 1476 0.0 168526.2 1.0X
UTF-8 is set 98848 100183 1592 0.0 197696.0 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 ...
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
Select a subset of 10 columns: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
Select 10 columns 13930 13996 60 0.7 1393.0 1.0X
Select 1 column 17092 17394 360 0.6 1709.2 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 ...
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
creation of JSON parser per line: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
Short column without encoding 5596 5711 101 1.8 559.6 1.0X
Short column with UTF-8 7983 8158 160 1.3 798.3 0.7X
Wide column without encoding 110189 118451 NaN 0.1 11018.9 0.1X
Wide column with UTF-8 137827 142813 NaN 0.1 13782.7 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 ...
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
JSON functions: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
Text read 951 953 2 10.5 95.1 1.0X
from_json 13015 13045 27 0.8 1301.5 0.1X
json_tuple 16257 16306 43 0.6 1625.7 0.1X
get_json_object 13195 13225 39 0.8 1319.5 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 ...
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
Dataset of json strings: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
Text read 4632 4687 49 10.8 92.6 1.0X
schema inferring 29176 29297 146 1.7 583.5 0.2X
parsing 24268 24457 175 2.1 485.4 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 ...
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
Json files in the per-line mode: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
[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
Text read 8264 8272 7 6.1 165.3 1.0X
Schema inferring 31910 32375 543 1.6 638.2 0.3X
Parsing without charset 29290 29397 124 1.7 585.8 0.3X
Parsing with UTF-8 41301 41390 81 1.2 826.0 0.2X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
Write dates and timestamps: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
Create a dataset of timestamps 1149 1160 11 8.7 114.9 1.0X
to_json(timestamp) 11585 11688 140 0.9 1158.5 0.1X
write timestamps to files 10212 10260 49 1.0 1021.2 0.1X
Create a dataset of dates 1322 1328 10 7.6 132.2 0.9X
to_json(date) 7226 7241 14 1.4 722.6 0.2X
write dates to files 5634 5648 20 1.8 563.4 0.2X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_202-b08 on Mac OS X 10.14.4
Intel(R) Core(TM) i7-4850HQ CPU @ 2.30GHz
Read dates and timestamps: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
read timestamp text from files 2097 2137 41 4.8 209.7 1.0X
read timestamps from files 20438 20451 11 0.5 2043.8 0.1X
infer timestamps from files 41694 41770 66 0.2 4169.4 0.1X
read date text from files 1832 1847 16 5.5 183.2 1.1X
read date from files 13796 13837 49 0.7 1379.6 0.2X
timestamp strings 3213 3233 26 3.1 321.3 0.7X
parse timestamps from Dataset[String] 22686 22743 53 0.4 2268.6 0.1X
infer timestamps from Dataset[String] 45301 45368 58 0.2 4530.1 0.0X
date strings 3431 3439 7 2.9 343.1 0.6X
parse dates from Dataset[String] 17688 17734 41 0.6 1768.8 0.1X
from_json(timestamp) 33439 33456 24 0.3 3343.9 0.1X
from_json(date) 24055 24164 107 0.4 2405.5 0.1X
[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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