please update the product docs ( if not already done).
Also we should write an article.
On Tue, Sep 13, 2016 at 2:08 PM, Gokul Balakrishnan <go...@wso2.com> wrote:
> Hi all,
> The objective of this mail is to summarise the results of the recently
> conducted performance test round for DAS 3.1.0.
> These tests were intended to measure the throughput of the batch and
> interactive analytics capabilities of DAS under different conditions;
> namely data persistence, Spark analytics job execution and indexing. For
> this purpose, we've used DAS 3.1.0 RC3 instances backed by an Apache HBase
> cluster running on HDFS as the data store, tuned for writes.
> This test round was conducted on Amazon EC2 nodes, in the following
> 3 DAS nodes (variable roles: publisher, receiver, analyzer and indexer):
> 1 HBase master + Hadoop Namenode: c3.2xlarge
> 9 HBase Regionservers + Hadoop Datanodes: c3.2xlarge
> *1. Persisting 1 billion events from the Smart Home DAS sample*
> This test was designed to test the data layer during sustained event
> publication. During testing, the TPS was around the 150K mark, and the
> HBase cluster's memstore flush (which suspends all writes) and minor
> compaction operations brought it down somewhat in bursts. Overall, we were
> able to achieve a mean of 96K TPS, but a steady rate of around 100-150K TPS
> as is achievable, as opposed to the current no-flow-control situation.
> The published data took around 950GB on the Hadoop filesystem, taking
> HDFS-level replication into account.
> Events 1000000000
> Time (s) 10391.768
> Mean TPS 96230.01591
> *2. Analyzing 1 billion events through Spark*
> Spark queries from the Smart Home DAS sample were executed against the
> published data, and the analyzer node count was kept 2 and 3 respectively
> for 2 separate tests. We'd given 6 processor cores and 12GB dedicated
> memory for the Spark JVM during this test, and were able to get a
> throughput of over 1M TPS on Spark for 2 analyzers and about 1.3M TPS for 3
> DAS read operations from the HBase cluster also leverage HBase data
> locality, which would have made the read process more efficient compared to
> random reads.
> The mean throughput readings from 3 tests at each case with a query
> involving aggregate functions and GROUP BY are as follows:
> INSERT OVERWRITE TABLE cityUsage SELECT metro_area, avg(power_reading) AS
> min(power_reading) AS min_usage, max(power_reading) AS max_usage FROM
> smartHomeData GROUP BY metro_area ;
> 2 Analyzer Nodes 3 Analyzer Nodes
> Records 1000000000 1000000000
> Time (s) 958.802 741.152
> Mean TPS 1042968.204 1349250.896
> *3. Persisting the entire Wikipedia corpus*
> This test involved publishing the entirety of the Wikipedia dataset, where
> a single event comprises of one Wiki article (16.8M articles in total).
> Events vary greatly in size, with the mean being ~3.5KB; hence, the
> throughput also varies greatly as expected. Here, we were able to see a
> mean throughput of around 9K TPS:
> Events 16753779
> Time (s) 1862.901
> Mean TPS 8993.381291
> *4. Indexing the full Wikipedia dataset*
> In this test, the data from the Wikipedia dataset was indexed, whereby the
> articles would support full text search through Lucene. The index worker
> counts of 2 and 4 were tested, and 2 dedicated indexer nodes were used in
> the test to run the indexing jobs independently to each other.
> The TPS v time graph of the first indexer node with 4 dedicated index
> worker threads is as below:
> The overall results from both indexer nodes can be summarised as below:
> Records 16753779
> Node 2 Worker threads 4 worker threads
> Indexer 1 2198.66 TPS
> 2268.62 TPS
> Indexer 2 4230.75 TPS
> 3048.91 TPS
> *5. Analyzing the Wikipedia dataset*
> Similar to the Smart Home dataset, Spark queries were run against the
> published Wikipedia dataset, using analyzer clusters of 2 and 3 nodes
> respectively. The results of one of these tests are as follows:
> INSERT INTO TABLE wikiContributorSummary SELECT contributor_username,
> COUNT(*) as page_count FROM wiki GROUP BY contributor_username;
> Records 16753779
> Node 2 Analyzer Nodes 4 Analyzer Nodes
> Time (s)
> TPS 70958.41716
> The full findings of this test may be found in the attached Spreadsheet.
> Best regards,
> Testing DAS 3.1.0 Performance on a 10-node HBas...
> Gokul Balakrishnan
> Senior Software Engineer,
> WSO2, Inc. http://wso2.com
> M +94 77 5935 789 | +44 7563 570502
Srinath Perera, Ph.D.
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