Is hadoop maintained?

2019-07-04 Thread Yuri
I created this bug report, in an attempt to fix the FreeBSD port: https://issues.apache.org/jira/browse/HADOOP-16388 but there was no answer. Does anybody know if Hadoop is a maintained project, and if yes, how to get a hold of somebody who can help with this bug? Thank you, Yuri

Re: BlockPlacementPolicy question with hierarchical topology

2019-07-04 Thread Takanobu Asanuma
Oh, you are right. It doesn't meet your needs. Sorry for the confusion. Seems it may be difficult to achive it with the existing policies. - Takanobu From: Lars Francke Sent: Thursday, July 4, 2019 7:53:35 PM To: 浅沼 孝信 Cc: hdfs-user@hadoop.apache.org

Re: BlockPlacementPolicy question with hierarchical topology

2019-07-04 Thread Lars Francke
Hi Takanobu, thanks for the quick reply. I missed that class. But does it really do what I need? If I have these racks: /dc1/rack1 /dc1/rack2 /dc1/rack3 /dc2/rack1 /dc2/rack2 /dc2/rack3 And I place a single block in HDFS, couldn't this policy chose /dc1/rack1, /dc1/rack2, /dc1/rack3 at random?

Re: BlockPlacementPolicy question with hierarchical topology

2019-07-04 Thread Takanobu Asanuma
Hi Lars, I think BlockPlacementPolicyRackFaultTolerant can do it. This policy tries to place 3 replica separately in different racks. dfs.block.replicator.classname org.apache.hadoop.hdfs.server.blockmanagement.BlockPlacementPolicyRackFaultTolerant See also:

BlockPlacementPolicy question with hierarchical topology

2019-07-04 Thread Lars Francke
Hi, I have a customer who wants to make sure that copies of his data are distributed amongst datacenters. So they are using rack names like this /dc1/rack1, /dc1/rack2, /dc2/rack1 etc. Unfortunately, the BlockPlacementPolicyDefault seems to place all blocks on /dc1/* sometimes. Is there a way

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2019-07-04 Thread 1427357147
unsubscribe -- -- ??: "kevin su"; : 2019??7??4??(??) 7:11 ??: "user@hadoop.apache.org"; : Dose Yarn shared cache use memory ? Hi all, I want make sure that yarn shared cache and distributed cache whether used memory or