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https://issues.apache.org/jira/browse/SOLR-1301?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12753332#action_12753332
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jv ning commented on SOLR-1301:
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In my case, I have 6 tasks per machine, but only 4 disks, so I should
actually throttle.
It is an interesting trade of question of whether to make the writes run in
the background or to just block the job.
In operation on my cluster, the write time for each batch increases slowly
from nothing to 20 minutes as the job runs, and the system buffer cache and
the disk arms get saturated.
I also was lazy and didn't feel like holding exceptions from a background
writing thread and delivering them back to the writing thread, on the next
write or close call.
There are some operational hadoop api features that make the assumption that
an error is associated with the key, value that is being output. On the flip
side the buffered batch is already hiding potential errors associated with a
specific record...
The case you are referring to would be the MultiThreadedMapper case which is
not used widely, the only change for that, which I should have done, is make
the write and close thread safe, which they are explicitly not right now.
> Solr + Hadoop
> -------------
>
> Key: SOLR-1301
> URL: https://issues.apache.org/jira/browse/SOLR-1301
> Project: Solr
> Issue Type: Improvement
> Affects Versions: 1.4
> Reporter: Andrzej Bialecki
> Attachments: hadoop-0.19.1-core.jar, hadoop.patch, solr.zip
>
>
> This patch contains a contrib module that provides distributed indexing
> (using Hadoop) to Solr EmbeddedSolrServer. The idea behind this module is
> twofold:
> * provide an API that is familiar to Hadoop developers, i.e. that of
> OutputFormat
> * avoid unnecessary export and (de)serialization of data maintained on HDFS.
> SolrOutputFormat consumes data produced by reduce tasks directly, without
> storing it in intermediate files. Furthermore, by using an
> EmbeddedSolrServer, the indexing task is split into as many parts as there
> are reducers, and the data to be indexed is not sent over the network.
> Design
> ----------
> Key/value pairs produced by reduce tasks are passed to SolrOutputFormat,
> which in turn uses SolrRecordWriter to write this data. SolrRecordWriter
> instantiates an EmbeddedSolrServer, and it also instantiates an
> implementation of SolrDocumentConverter, which is responsible for turning
> Hadoop (key, value) into a SolrInputDocument. This data is then added to a
> batch, which is periodically submitted to EmbeddedSolrServer. When reduce
> task completes, and the OutputFormat is closed, SolrRecordWriter calls
> commit() and optimize() on the EmbeddedSolrServer.
> The API provides facilities to specify an arbitrary existing solr.home
> directory, from which the conf/ and lib/ files will be taken.
> This process results in the creation of as many partial Solr home directories
> as there were reduce tasks. The output shards are placed in the output
> directory on the default filesystem (e.g. HDFS). Such part-NNNNN directories
> can be used to run N shard servers. Additionally, users can specify the
> number of reduce tasks, in particular 1 reduce task, in which case the output
> will consist of a single shard.
> An example application is provided that processes large CSV files and uses
> this API. It uses a custom CSV processing to avoid (de)serialization overhead.
> This patch relies on hadoop-core-0.19.1.jar - I attached the jar to this
> issue, you should put it in contrib/hadoop/lib.
> Note: the development of this patch was sponsored by an anonymous contributor
> and approved for release under Apache License.
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