Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations.

To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark spark.

Project Site

spark.apache.org

Source Repository

github.com

Test Created

4 August 2022

Last Updated

20 January 2023

Test Maintainer

Michael Larabel 

Test Type

System

Average Install Time

4 Seconds

Average Run Time

47 Minutes, 28 Seconds

Test Dependencies

Java + Python

Accolades

30k+ Downloads

Supported Platforms


Public Result Uploads *Reported Installs **Reported Test Completions **Test Profile Page ViewsOpenBenchmarking.orgEventsApache Spark Popularity Statisticspts/spark2022.082022.092022.102022.112022.122023.012023.022023.032023.042023.052023.062023.072023.082023.092023.102023.112023.122024.012024.022024.032024.042024.052024.065K10K15K20K25K
* Uploading of benchmark result data to OpenBenchmarking.org is always optional (opt-in) via the Phoronix Test Suite for users wishing to share their results publicly.
** Data based on those opting to upload their test results to OpenBenchmarking.org and users enabling the opt-in anonymous statistics reporting while running benchmarks from an Internet-connected platform.
Data updated weekly as of 15 June 2024.
2000000021.5%1000000022.5%100000033.6%4000000022.4%Row Count Option PopularityOpenBenchmarking.org
10031.1%200024.8%50022.6%100021.5%Partitions Option PopularityOpenBenchmarking.org

Revision History

pts/spark-1.0.1   [View Source]   Fri, 20 Jan 2023 07:57:46 GMT
Update download mirror for Spark 3.3.0. Closes: https://github.com/phoronix-test-suite/test-profiles/issues/265

pts/spark-1.0.0   [View Source]   Thu, 04 Aug 2022 04:35:20 GMT
Initial commit of Apache Spark benchmark.

Suites Using This Test

Database Test Suite

Server


Performance Metrics

Analyze Test Configuration:

Apache Spark 3.3

Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark

OpenBenchmarking.org metrics for this test profile configuration based on 434 public results since 4 August 2022 with the latest data as of 14 April 2024.

Below is an overview of the generalized performance for components where there is sufficient statistically significant data based upon user-uploaded results. It is important to keep in mind particularly in the Linux/open-source space there can be vastly different OS configurations, with this overview intended to offer just general guidance as to the performance expectations.

Component
Percentile Rank
# Compatible Public Results
Seconds (Average)
Mid-Tier
75th
> 66
Median
50th
110
39th
12
148 +/- 10
38th
7
157 +/- 5
31st
8
187 +/- 1
Low-Tier
25th
> 229
25th
9
230 +/- 23
24th
7
231 +/- 3
22nd
8
242 +/- 6
20th
5
251 +/- 1
19th
3
265 +/- 1
16th
3
305 +/- 3
15th
7
317 +/- 15
13th
5
334 +/- 1
12th
6
359 +/- 22
12th
3
374 +/- 1
8th
10
405 +/- 29
4th
4
584 +/- 6
2nd
3
709 +/- 50
OpenBenchmarking.orgDistribution Of Public Results - Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark434 Results Range From 9 To 2802 Seconds965121177233289345401457513569625681737793849905961101710731129118512411297135314091465152115771633168917451801185719131969202520812137219322492305236124172473252925852641269727532809306090120150

Based on OpenBenchmarking.org data, the selected test / test configuration (Apache Spark 3.3 - Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark) has an average run-time of 16 minutes. By default this test profile is set to run at least 3 times but may increase if the standard deviation exceeds pre-defined defaults or other calculations deem additional runs necessary for greater statistical accuracy of the result.

OpenBenchmarking.orgMinutesTime Required To Complete BenchmarkRow Count: 1000000 - Partitions: 100 - Calculate Pi BenchmarkRun-Time20406080100Min: 2 / Avg: 15.24 / Max: 104

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.1%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsRow Count: 1000000 - Partitions: 100 - Calculate Pi BenchmarkDeviation246810Min: 0 / Avg: 0.14 / Max: 2

Does It Scale Well With Increasing Cores?

Yes, based on the automated analysis of the collected public benchmark data, this test / test settings does generally scale well with increasing CPU core counts. Data based on publicly available results for this test / test settings, separated by vendor, result divided by the reference CPU clock speed, grouped by matching physical CPU core count, and normalized against the smallest core count tested from each vendor for each CPU having a sufficient number of test samples and statistically significant data.

IntelAMDOpenBenchmarking.orgRelative Core Scaling To BaseApache Spark CPU Core ScalingRow Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark4812162432641283691215

Tested CPU Architectures

This benchmark has been successfully tested on the below mentioned architectures. The CPU architectures listed is where successful OpenBenchmarking.org result uploads occurred, namely for helping to determine if a given test is compatible with various alternative CPU architectures.

CPU Architecture
Kernel Identifier
Verified On
Intel / AMD x86 64-bit
x86_64
(Many Processors)
ARMv8 64-bit
aarch64
ARMv8 Cortex-A72, ARMv8 Cortex-A76 4-Core, ARMv8 Neoverse-N1, ARMv8 Neoverse-N1 128-Core, ARMv8 Neoverse-N1 64-Core, ARMv8 Neoverse-N2, ARMv8 Neoverse-V1, ARMv8 Neoverse-V1 64-Core, Apple M1, Apple M2, Rockchip ARMv8 Cortex-A76 4-Core, rk1-mainline-emmc, rk1-mainline-nvme, rk1-rok-emmc

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