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05-30-2018
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715
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148
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My Accepted Solutions
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4072 | 07-19-2018 12:52 PM |
02-17-2016
09:47 PM
3 Kudos
Is ranger able to control security at a namespace level within hbase?
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Apache HBase
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Apache Ranger
02-17-2016
09:26 PM
2 Kudos
It appear spark does not leverage full R and python libraries. I would like to understand why. Any feedback?
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Apache Spark
02-17-2016
02:14 AM
2 Kudos
Does ranger enforce policies on phoenix which are created via ranger for hbase?
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Apache HBase
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Apache Phoenix
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Apache Ranger
02-16-2016
03:52 AM
2 Kudos
I read in this tutorial http://hortonworks.com/hadoop-tutorial/supercharging-interactive-queries-hive-tez/ about Multi-tenancy with HiveServer2
There could be contentions when multiple users run large queries simultaneously. Processing queries with many containers could lead to lower latency. For this, 3 controls could be put in place:
Container re-use timeout
Tez split wave tuning
Round Robin Queuing setup
What is Round Robin Queuing Setup within Hive/Tez? How would one go about the setup? No details were provided.
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Apache Hive
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Apache Tez
02-11-2016
04:09 AM
1 Kudo
@Neeraj Sabharwal I like this. Can you explain the reason for -d statusdir="1p"?
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02-10-2016
08:53 PM
1 Kudo
done. https://community.hortonworks.com/articles/16151/yarn-que-utilization-ambari-widget.html
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02-10-2016
08:51 PM
5 Kudos
Using ambari metrics we are able to determine queue utilization. Here is how I did it. Determine which queue you need to run analysis against create a widget Add this widget to any dash board..For example You can view the utilization by time using the drop down:
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02-10-2016
08:42 PM
1 Kudo
@Neeraj Sabharwal Yes I do. You think it is better off as a article?
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02-10-2016
06:10 PM
3 Kudos
@Neeraj Sabharwal I created a widget to do this: and then I added this widget to my yarn page. You can view the utilization by time using the drop down:
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02-10-2016
03:33 PM
1 Kudo
Multi-thread support is provided via the concurrent tasks configuration parameter on a processor. Think of as being able to run multiple copies of the same processor in parallel on the same NiFi instance. Each thread is not tied to one another, so no file chunking occurs here. NiFi works on batches of files to be more efficient, so multiple thread would allow a processors to work on multiple batches at the same time. So in the case of a putSFTP, multiple connections will be established with destination at the same time sending multiple batches of files. If the network bandwidth exists, this can result in a considerable increase in overall throughput.
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