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From "Jason Rutherglen (JIRA)" <j...@apache.org>
Subject [jira] Commented: (SOLR-1301) Solr + Hadoop
Date Fri, 15 Jan 2010 17:36:54 GMT

    [ https://issues.apache.org/jira/browse/SOLR-1301?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12800775#action_12800775
] 

Jason Rutherglen commented on SOLR-1301:
----------------------------------------

{quote}What I meant was the Hadoop job could simply know what
the set of master indexers are and send the documents directly
to them{quote}

One can use Hadoop for this purpose, we have implemented the
system in this way for the incremental indexes, however it
doesn't require a separate patch or contrib module. The problem
with the Hadoop streaming model is it doesn't scale well, if for
example, we need to reindex using the CJKAnalyzer, or using
Basis' analyzer etc. We use SOLR-1301 for reindexing loads of
data, as fast as possible by parallelizing the indexing. There
are lots of little things I'd like to add to the functionality,
though, implementing ZK based core management takes a higher
priority, as I spend a lot of time doing this manually today.

> 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 
>             Fix For: 1.5
>
>         Attachments: commons-logging-1.0.4.jar, commons-logging-api-1.0.4.jar, hadoop-0.19.1-core.jar,
hadoop.patch, log4j-1.2.15.jar, README.txt, SOLR-1301.patch, SOLR-1301.patch, SOLR-1301.patch,
SOLR-1301.patch, SOLR-1301.patch, SolrRecordWriter.java
>
>
> 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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