Member since
10-24-2017
38
Posts
1
Kudos Received
0
Solutions
03-13-2020
09:04 AM
Be careful with setting ParallelGCThreads to 8 as it will decrease threads if the system has more processing power. => https://docs.oracle.com/javase/8/docs/technotes/guides/vm/gctuning/parallel.html On a machine with N hardware threads where N is greater than 8, the parallel collector uses a fixed fraction of N as the number of garbage collector threads. The fraction is approximately 5/8 for large values of N. At values of N below 8, the number used is N. On selected platforms, the fraction drops to 5/16. The specific number of garbage collector threads can be adjusted with a command-line option (which is described later). On a host with one processor, the parallel collector will likely not perform as well as the serial collector because of the overhead required for parallel execution (for example, synchronization). However, when running applications with medium-sized to large-sized heaps, it generally outperforms the serial collector by a modest amount on machines with two processors, and usually performs significantly better than the serial collector when more than two processors are available.
... View more
05-14-2018
04:45 PM
that worked. thanks for the help
... View more
04-13-2018
06:20 AM
Error shows process is not able to get the required memory from system. Ideally HBASE_HEAPSIZE should have helped. By default, hbase hbck will use default heap size of JVM which is usually ~1GB. You can try setting below option and then try executing hbck. export _JAVA_OPTIONS="-Xmx1024m -Xms1024m" hbase hbck Note : You can try different values of heap in _JAVA_OPTIONS
... View more
01-12-2018
07:23 PM
Thanks for answering my question. The community has been answering my questions in a short time. Keep up the good work!
... View more
01-09-2018
04:35 AM
@prarthana basgod As the official HBase book states: You may need to find a sweet spot between a low number of RPCs and the memory used on the client and server. Setting the scanner caching higher will improve scanning performance most of the time, but setting it too high can have adverse effects as well: each call to next() will take longer as more data is fetched and needs to be transported to the client, and once you exceed the maximum heap the client process has available it may terminate with an OutOfMemoryException. When the time taken to transfer the rows to the client, or to process the data on the client, exceeds the configured scanner lease threshold, you will end up receiving a lease expired error, in the form of a ScannerTimeoutException being thrown. So it would be better not to avoid the exception by the above configuration, but to set the caching of your Map side lower, enabling your mappers to process the required load into the pre-specified time interval. Even you can increase <property>
<name>hbase.regionserver.lease.period</name>
<value>300000</value>
</property> Hope this helps you.
... View more