Hi Bala/Srihari In the Drill query profile, I dont see the query running for more than a second. The example you gave is with 350msec. I'm not sure what the backend Mongo storage plugin is doing. You'll probably need to profile the Drillbit using something like Yourkit or JVisualVM to identify what threads are burning CPU and the possible hotspots. I dont see anything hinting at a problem.
Kunal On 10/20/2018 12:30:50 AM, Srihari Prabhakar <sriharip...@gmail.com> wrote: Hi Kunal, I have Web UI enabled, but queries are not being run from there. Queries are being run through JDBC. Attaching the Drill query, drill profile. Also I have enabled profiling on MongoDB and captured all the queries triggered by drill on MongoDB. I have grouped all MongoDB queries by shape and taken the count of each query. If I understand correctly, drill doesn't store MongoDB schema, so one count query and one simple find on collection is expected, as it has to capture schema information. But, I see count and find being run 43 times each for one single query in drill. On Sat, 20 Oct 2018 at 00:06, Kunal Khatua <ku...@apache.org [mailto:ku...@apache.org]> wrote: Hi Bala Can you share details of the profiles itself? It might be that the MongoDB storage plugin is translating the query into 100 mongo queries because of some (100?) specific filter criteria in the Drill query? JVM Heap usage fluctuation would indicate frequent object creation and garbage collection, probably by the Mongo storage plugin itself. Are you running the query through the WebUI or via JDBC? As long as you are not seeing any GC logs indicating a leak in the heap memory, the heap usage fluctuating is normal for your 6GB heap allocation. If you are using the WebUI or REST API, it is possible that there is overhead in Drill rendering the resultset that can cause higher heap and CPU usage. On 10/18/2018 1:10:25 PM, Balasubramanian Naganathan <balsu1...@gmail.com [mailto:balsu1...@gmail.com]> wrote: Hello, We have tableau BI tool which is getting data from MongoDB using Apache drill. We are running drill on 5 nodes each having 8 core and 16 GB RAM, but they are not running as a cluster. Each node is an individual instance. We have a Load Balancer to load balance across these 5 nodes. /usr/lib/jvm/java-1.8.0-openjdk-1.8.0.181-3.b13.el7_5.x86_64/jre/bin/java -Xms6G -Xmx6G -XX:MaxDirectMemorySize=13G -XX:ReservedCodeCacheSize=1024m -Ddrill.exec.enable-epoll=false -Dproperty=value -Duser.timezone=UTC -XX:+UseStringDeduplication -Dproperty=value -Duser.timezone=UTC -Duser.timezone=UTC -Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.port=27017 -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.ssl=false -XX:+UseG1GC -Dlog.path=/opt/apache-drill-1.14.0/log/drillbit.log -Dlog.query.path=/opt/apache-drill-1.14.0/log/drillbit_queries.json -cp /opt/apache-drill-1.14.0/conf:/opt/apache-drill-1.14.0/jars/*:/opt/apache-drill-1.14.0/jars/ext/*:/opt/apache-drill-1.14.0/jars/3rdparty/*:/opt/apache-drill-1.14.0/jars/classb/*:/opt/apache-drill-1.14.0/jars/3rdparty/linux/* org.apache.drill.exec.server.Drillbit We see that apache drill is reaching 100% CPU when we run 30 queries per second. All the queries are very simple queries without any aggregation. Also each query in Apache drill is getting converted to 100 queries in Mongo. 97% of the queries are find(1) and count() mongoDB Queries. Not sure why they are triggered. Also we tried adding "-XX:+UseStringDeduplication", JVM parameter, We saw the load become uneven after adding this parameter. Are there any other JVM parameters that we can add to improve drill performance? Even though there are no calls to drill, the heap memory usage is fluctuating. It goes up to around 70% (~4GB) and comes back to around 1GB. Thanks, Bala
