The best way is to use a profiler to understand where time is spent.
Spark while it is significantly faster than Hadoop, cannot compete with CULR.
The latter is a simple REST connection - the former triggers a JVM, Scala, akka, Spark,
which triggers es-hadoop which does the parallel call against all the nodes, retries the data in JSON format,
converts it into Scala/Java and applies on schema on top for Spark SQL to run with.
If you turn on logging, you'll see in fact there are multiple REST/CURL calls done by es-hadoop.
With a JVM/Scala warmed up, you should see less than 15s however it depends on how much hardware you have available.
Note that the curl comparison is not really fair - adding a SQL layer on top of that is bound to cost you something.
On 6/1/15 8:47 PM, Dmitriy Fingerman wrote:
> Hi,
>
> I see a big difference in performance of the same query expressed via Spark SQL and CURL.
> In CURL the query runs less then a second, and in Spark SQL it runs 15 seconds.
> The index/type which I am querying contains 1M documents.
> Can you please explain why there is so big difference in performance?
> Are there any ways to tune performance of Elasticsearch + Spark SQL?
>
> Environment: (everything is running on the same box):
> Elasticsearch 1.4.4
> elasticsearch-hadoop 2.1.0.BUILD-SNAPSHOT
> Spark 1.3.0.
>
> CURL:
>
> curl -XPOST "
http://localhost:9200/summary/intervals/_search" -d'
> {
> "query" : {
> "filtered" : {
> "query" : { "match_all" : {}},
> "filter" : {
> "bool" : {
> "must" : [
> {
> "term" : { "User" : "Robert Greene" }
> },
> {
> "term" : { "DataStore" : "PROD_HK_HR" }
> },
> {
> "term" : { "EventAffectedCount" : 56 }
> }
> ]
> }
> }
> }
> }
> }'
>
> Spark:
>
> val sparkConf = new SparkConf().setAppName("Test1")
>
> // increasing scroll size to 5000 from the default 50 improved performance by 2.5 times
> sparkConf.set("es.scroll.size", "5000")
>
> val sc = new SparkContext(sparkConf)
> val sqlContext = new SQLContext(sc)
>
> val intv = sqlContext.esDF("summary/intervals")
> intv.registerTempTable("INTERVALS")
>
> val intv2 = sqlContext.sql("select EventCount, Hour " +
> "from intervals " +
> "where User = 'Robert Greene' " +
> "and DataStore = 'PROD_HK_HR' " +
> "and EventAffectedCount = 56 ")
> intv2.show(1000)
>
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