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官方 TEZUI 需要TEZ6+hadoop2.6.0
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其实 TEZUI TEZ0.53+hadoop2.4.0+也可以玩 只要hadoop有timelineserver
但是hadoop2.4.0 hadoop2.5.0 timelineserver不支持跨域请求。。所以用ambari2.2中的tez view来搭建可以实现，并且方便快捷。
tez-site.xml
yarn-site.xml
加上
If enabled, the TimelineClient library used by end-users will post entities
and events to the Timeline server.
cross-origin web response headers are needed. For example, javascript making
a web services request to the timeline server.
http://search-hadoop.com/m/tQlTsMD%26subj=Tez+nbsp+taskcount+log+visualization
yarn timelineserver start 可以启动timelineserver
Tez config
https://issues.apache.org/jira/browse/TEZ-2294
Tez 优化
Listing some details at very high level,
- Set "tez.task.generate.counters.per.io=true" to get more details on the task counters. Basically this starts printinng the counters per edge, which can be a lot more useful for debugging.
- In case you want to avoid container launches etc when you analyze for first time, try hive.prewarm.enabled=true & hive.prewarm.numcontainers=
- Container reuse is enabled by default in tez. (tez.am.container.idle.release-timeout-min.millis, tez.am.container.idle.release-timeout-max.millis controls the amount of time a container is held by AM before releasing it)
- Set tez.runtime.io.sort.mb appropriately to avoid spills (you can check task counters in the logs to find out the spills and adjust it accordingly)
- Set tez.runtime.sort.threads=2 to enable PipelinedSorter which is a lot performant than DefaultSorter (this is the default in master branch. But if you are using earlier releases, you can turn it on by setting tez.runtime.sort.threads=2).
- Set tez.runtime.compress=true and set tez.runtime.compress.codec (SnappyCodec is preferred, but it is upto you to choose)
- Set tez.runtime.shuffle.keep-alive.enabled=true in case you have shuffle heavy workload. This reduces number of connections in shuffle.
- Adjust memory allocated to different inputs/outputs based on tez.task.scale.memory.ratios (but this is more of expert level setting which you might want to touch after nailing down any memory pressure)
- Adjusting shuffle buffers are also possible, but would advise only when you nail down an issue related to shuffle/merge codepath.
- Set "tez.runtime.optimize.local.fetch=true" to bypass http fetches (when data is locally present)
Feel free to refer to https://github.com/t3rmin4t0r/tez-autobuild/blob/master/tez-site.xml for any commonly used settings for benchmarks.
Rajesh,
What are the problems with having tez.runtime.shuffle.keep-alive.enabled and tez.runtime.optimize.local.fetch set to true always by default?
@r7raul1984, would you mind filing a documentation jira for your question. The list that Rajesh provided might be good to formalize into a doc and/or wiki.
Also, please take a look at https://issues.apache.org/jira/browse/TEZ-2294 to see all the list of parameters. If you see something off or not clear enough, please add your comments to the jira.
@Rohini,
We recently changed tez.runtime.optimize.local.fetch to true as the default value in master. The feature was introduced and probably kept as false initially as it had not been fully battle tested.
The latter I am assuming depends on how many open connections a cluster’s setup can sustain and needs to be tuned in combination with “tez.runtime.shuffle.keep-alive.max.connections”. Good point on whether we should make this true by default. Will wait for @Rajesh/@Gopal/@Sid to chime in and they can open a new jira if this is generally beneficial in most setups.
> What are the problems with having
>tez.runtime.shuffle.keep-alive.enabled and
>tez.runtime.optimize.local.fetch set to true always by default?
> What are the problems with having
>tez.runtime.shuffle.keep-alive.enabled and
>tez.runtime.optimize.local.fetch set to true always by default?
Nothing has failed due to these so far - we
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