Re: Disable WriteBehind

Hi, please see the log attached. On Fri, Apr 14, 2017 at 9:07 AM, Nikolai Tikhonov-2 [via Apache Ignite Users] wrote: > Yes, Ignite.log. > > On Fri, Apr 14, 2017 at 6:54 PM, waterg <[hidden email] > > wrote: >

LocalDateTime field being ignored on Cassandra write through

Hello, I am running some tests using the Cassandra as persistent storage using CassandraCacheStoreFactory, however the LocalDateTime field is ignored, I've tried having the table automatically defined and the field is not created, I have also manually defined the table, however the value passed is

Re: Index

See attached screenshot - how to check indexes. -- View this message in context: http://apache-ignite-users.70518.x6.nabble.com/Index-tp11969p11985.html Sent from the Apache Ignite Users mailing list archive

Re: Disable WriteBehind

Yes, Ignite.log. On Fri, Apr 14, 2017 at 6:54 PM, waterg wrote: > Hi Nikolai, No topology changes. We have 2 server nodes and a client node. > > What kind of log you refer to? Ignite log? > > Jessie > > On Fri, Apr 14, 2017 at 6:52 AM, Nikolai Tikhonov-2 [via

Re: Disable WriteBehind

Hi Nikolai, No topology changes. We have 2 server nodes and a client node. What kind of log you refer to? Ignite log? Jessie On Fri, Apr 14, 2017 at 6:52 AM, Nikolai Tikhonov-2 [via Apache Ignite Users] wrote: > Hello! > > Was topology stable? Could you

Re: Persisting data to cassandra tables.

Hi, Please properly subscribe to the mailing list so that the community can receive email notifications for your messages. To subscribe, send empty email to user-subscr...@ignite.apache.org and follow simple instructions in the reply. Jenny B. wrote > Hi > > I am writing this test for a POC

Re: ScanQuery log all entries

Hi Sam, 1. Yes getAll() will bring all values to an on-heap collection, which may lead to OOME, so it should be used with caution. 2. Any query returns QueryCursor that lazily iterates over entries. You may do 1000 iterations over cursor and accumulate result in some collection. This will be just

Re: Index

Hi Sambhav, You may find created indexes using web-console [1]. [1] https://ignite.apache.org/addons.html#web-console -Dmitry -- View this message in context: http://apache-ignite-users.70518.x6.nabble.com/Index-tp11969p11980.html Sent from the Apache Ignite Users mailing list archive at

Re: Disable WriteBehind

Hello! Was topology stable? Could you share full logs for this case? On Thu, Apr 13, 2017 at 8:36 PM, waterg wrote: > Hello Nikolai, > > Thank you for your reply. > I'm working a simplified maven project, to reproduce. > Btw, with this configuration below, we did

Re: Basic question on scaling of reads with ignite sql queries

Hi, Please properly subscribe to the mailing list so that the community can receive email notifications for your messages. To subscribe, send empty email to user-subscr...@ignite.apache.org and follow simple instructions in the reply. Yes, for now, query will be send to all Item cache data

Re: Ignite Node Discovery IP config

Hi Ramzinator, This will not work in that way. All nodes in grid should be able to see each other as via dicovery ports as via communication ports. Node1 starts and found no one. So, you have first grid. Node2 starts and found no one. Now, you have second grid. Node3 starts and join to one of

RE: OOM when using Ignite as HDFS Cache

Hi, The correct way here would be to understand where actually problem occurs and after that make decisions on how to solve it. > I also notice that Ignite write through file block size is set to 64MB. I > mean I write a file to Ignite with block size to 4GB, but I finally found > it on HDFS

RE: OOM when using Ignite as HDFS Cache

I'm using the latest version of JDK, AKA. 1.8.0_121 The cache is aim to provide a faster read/write performance. But the availability is more important. 1GB cache is for testing purpose. But it's the same issue if I write a 1TB file to 64GB cache. What I mean availability is that Ignite should

Re: OOM when using Ignite as HDFS Cache

I would not expect any of the things that you mention. A cache is not supposed to slow down writing. This does not make sense from my point of view. Splitting a block into several smaller ones is also not feasible. The data has to go somewhere before splitting. I think what you refer to is

RE: OOM when using Ignite as HDFS Cache

I think it's a kind of misconfiguration. The Ignite document just mentioned about how to configuration HDFS as a secondary filesystem but nothing about how to restrict the memory usage to avoid OOME. https://apacheignite.readme.io/v1.0/docs/igfs-secondary-file-system Assume I configured the