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https://issues.apache.org/jira/browse/CASSANDRA-11542?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15263494#comment-15263494
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Stefania commented on CASSANDRA-11542:
--------------------------------------
These are the results with the Spark Connector modified to support the
streaming proof of concept. Results are in seconds and represent the average of
5 different runs, see [^spark-load-perf-results-002.zip] for the raw data.
The improvement is approximately 30% for the RDD tests and 60% for the DF
tests. Further, the data for schema 3 does not match the data observed in the
previous run and the high variance continues to be observed.
|| ||SCHEMA 1|| ||SCHEMA 2|| ||SCHEMA 3|| ||SCHEMA 4|| ||
|| Test|| Time|| Std. Dev|| Time|| Std. Dev||
Time|| Std. Dev|| Time|| Std. Dev||
| parquet_rdd|2.73|0.23|2.90|0.30|6.09|0.21|6.33|0.21|
| parquet_df|2.87|0.72|2.68|0.62|4.65|0.78|4.40|0.32|
| csv_rdd|5.31|0.21|5.18|0.24|6.58|0.11|6.50|0.12|
| csv_df|12.26|1.00|12.31|0.28|13.03|0.25|13.04|0.19|
| cassandra_rdd|49.72|2.80|46.57|2.77|19.75|0.58|39.83|18.72|
|cassandra_rdd_stream|35.20|3.61|32.45|1.13|15.47|1.32|27.78|8.20|
| cassandra_df|33.32|5.40|35.75|1.90|19.84|8.43|35.82|17.67|
|cassandra_df_stream|20.76|2.91|21.06|0.72|12.80|0.47|22.70|9.00|
I think there may be another dominating factor that explains these results,
aside from the time it takes to receive data from Cassandra. The fact that the
streaming improvement is more noticeable for DF rather than RDD tests, and
significantly less than that noticed for [cassandra-stress
benchmarks|https://issues.apache.org/jira/browse/CASSANDRA-9259?focusedCommentId=15228054&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15228054],
may indicate that data decoding client-side plays a bigger role than streaming
in the final performance results. I am going to attach flight recorder to a
Spark worker to see if this assumption is correct. I still think we need
CASSANDRA-11520 and CASSANDRA-11521, but I just want to make sure we tackle the
bigger "bang for the buck" first.
> Create a benchmark to compare HDFS and Cassandra bulk read times
> ----------------------------------------------------------------
>
> Key: CASSANDRA-11542
> URL: https://issues.apache.org/jira/browse/CASSANDRA-11542
> Project: Cassandra
> Issue Type: Sub-task
> Components: Testing
> Reporter: Stefania
> Assignee: Stefania
> Fix For: 3.x
>
> Attachments: spark-load-perf-results-001.zip,
> spark-load-perf-results-002.zip
>
>
> I propose creating a benchmark for comparing Cassandra and HDFS bulk reading
> performance. Simple Spark queries will be performed on data stored in HDFS or
> Cassandra, and the entire duration will be measured. An example query would
> be the max or min of a column or a count\(*\).
> This benchmark should allow determining the impact of:
> * partition size
> * number of clustering columns
> * number of value columns (cells)
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