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CouchDB River Plugin for elasticsearch
Java Python

README.md

CouchDB River Plugin for Elasticsearch

The CouchDB River plugin allows to automatically index couchdb and make it searchable using the excellent _changes stream couchdb provides.

Rivers are deprecated and will be removed in the future. Have a look at logstash couchdb changes input.

In order to install the plugin, run:

bin/plugin install elasticsearch/elasticsearch-river-couchdb/2.6.0

You need to install a version matching your Elasticsearch version:

Elasticsearch CouchDB River Plugin Docs
master Build from source See below
es-1.x Build from source 2.7.0-SNAPSHOT
es-1.6 2.6.0 2.6.0
es-1.5 2.5.0 2.5.0
es-1.4 2.4.2 2.4.2
es-1.3 2.3.0 2.3.0
es-1.2 2.2.0 2.2.0
es-1.0 2.0.0 2.0.0
es-0.90 1.3.0 1.3.0

To build a SNAPSHOT version, you need to build it with Maven:

mvn clean install
plugin --install river-couchdb \ 
       --url file:target/releases/elasticsearch-river-couchdb-X.X.X-SNAPSHOT.zip

Create river

Setting it up is as simple as executing the following against elasticsearch:

curl -XPUT 'localhost:9200/_river/my_db/_meta' -d '{
    "type" : "couchdb",
    "couchdb" : {
        "host" : "localhost",
        "port" : 5984,
        "db" : "my_db",
        "filter" : null
    },
    "index" : {
        "index" : "my_db",
        "type" : "my_db",
        "bulk_size" : "100",
        "bulk_timeout" : "10ms"
    }
}'

This call will create a river that uses the _changes stream to index all data within couchdb. Moreover, any "future" changes will automatically be indexed as well, making your search index and couchdb synchronized at all times.

The couchdb river is provided as a plugin (including explanation on how to install it).

On top of that, in case of a failover, the couchdb river will automatically be started on another elasticsearch node, and continue indexing from the last indexed seq.

Bulking

Bulking is automatically done in order to speed up the indexing process. If within the specified bulk_timeout more changes are detected, changes will be bulked up to bulk_size before they are indexed.

Since 1.3.0, by default, bulk size is 100. A bulk is flushed every 5s. Number of concurrent requests allowed to be executed is 1. You can modify those settings within index section:

{
    "type" : "couchdb",
    "index" : {
        "index" : "my_index",
        "type" : "my_type",
        "bulk_size" : 1000,
        "flush_interval" : "1s",
        "max_concurrent_bulk" : 3
    }
}

Filtering

The changes stream allows to provide a filter with parameters that will be used by couchdb to filter the stream of changes. Here is how it can be configured:

{
    "couchdb" : {
        "filter" : "test",
        "filter_params" : {
            "param1" : "value1",
            "param2" : "value2"
        }
    }
}

Script Filters

Filtering can also be performed by providing a script that will further process each changed item within the changes stream. The json provided to the script is under a var called ctx with the relevant seq stream change (for example, ctx.doc will refer to the document, or ctx.deleted is the flag if its deleted or not).

Any other script language supported by Elasticsearch may be used by setting the script_type parameter to the appropriate value.

If unspecified, the default is groovy. See Scripting documentation for details.

The ctx.doc can be changed and its value can will be indexed (assuming its not a deleted change). Also, if ctx.ignore is set to true, the change seq will be ignore and not applied.

Other possible values that can be set are ctx.index to control the index name to index the doc into, ctx.type to control the (mapping) type to index into, ctx._parent and ctx._routing.

Here is an example setting that adds field1 with value value1 to all docs:

{
    "type" : "couchdb",
    "couchdb" : {
        "script" : "ctx.doc.field1 = 'value1'"
    }
}

Basic Authentication

Basic Authentication can be used by passing the user and password attributes.

{
    "type" : "couchdb",
    "couchdb" : {
        "user" : "alice",
        "password" : "secret"
    }
}

HTTPS

To use HTTPS, pass the protocol field. Most likely, you will also have to change the port. If you have unfixable problems with the servers certificates for any reason, you can disable hostname verification by passing no_verify.

{
    "type" : "couchdb",
    "couchdb" : {
        "protocol" : "https",
        "port" : 443,
        "no_verify" : "true"
    }
}

Ignoring Attachments

You can ignore attachments as provided by couchDb for each document (_attachments field).

Here is an example setting that disable attachments for all docs:

{
  "type":"couchdb",
  "couchdb": {
    "ignore_attachments":true
  }
}

Note, by default, attachments are not ignored (false)

Heartbeat

By default, couchdb river set _changes API heartbeat to 10s. Since 1.3.0, an additional option has been added to control the HTTP connection timeout (default to 30s). you can control both settings using heartbeat and read_timeout options:

curl -XPUT 'localhost:9200/_river/my_db/_meta' -d '{
    "type" : "couchdb",
    "couchdb" : {
        "host" : "localhost",
        "port" : 5984,
        "db" : "my_db",
        "heartbeat" : "5s",
        "read_timeout" : "15s"
    }
}'

Starting at a Specific Sequence

The CouchDB river stores the last_seq value in a document called _seq in the _river index. You can use this fact to start or resume rivers at a particular sequence.

To have the CouchDB river start at a particular last_seq, create a document with contents like this:

curl -XPUT 'localhost:9200/_river/my_db/_seq' -d '
{
  "couchdb": {
    "last_seq": "100"
  }
}'

where 100 is the sequence number you want the river to start from. Then create the _meta document as before. The CouchDB river will startup and read the last sequence value and start indexing from there.

Examples

Indexing Databases with Multiple Types

A common pattern in CouchDB is to have a single database hold documents of multiple types. Typically each document will have a field containing the type of the document.

For example, a database of products from Amazon might have a book type:

{
  "_id": 1,
  "type" : "book",
  "author" : "Michael McCandless",
  "title" : "Lucene in Action"
}

and a CD type:

{
  "_id": 2,
  "type" : "cd",
  "artist" : "Tool",
  "title" : "Undertow"
}

Elasticsearch also supports multiple types in the same index and we need to tell ES where each type from CouchDB goes. You do this with a river definition like this:

{
  "type" : "couchdb",
  "couchdb" : {
    "host" : "localhost",
    "port" : 5984,
    "db" : "amazon",
    "script" : "ctx._type = ctx.doc.type"
  },
  "index" : {
    "index" : "amazon"
  }
}

Setting ctx._type tells Elasticsearch what type in the index to use. So if doc.type for a CouchDB changeset is "book" then Elasticsearch will index it as the "book" type.

The script block can be expanded to handle more complicated cases if your types don't map one-to-one between the systems.

If you need to also handle deleting documents from the right type in Elasticsearch, be aware that the above setup requires you to delete documents from CouchDB in a special way. If you use the DELETE HTTP verb with CouchDB you will break the above river as ES will be unable to determine what type you're trying to delete. Instead you must preserve some information about the document you deleted by using the CouchDB bulk document interface.

For example, to delete the above "cd" document, you must post a document like this to the CouchDB server, replacing the _rev field with the revision of the document you want to delete:

curl -XPOST http://localhost:5984/amazon/_bulk_docs -d '
{
  "docs" : [
    {
        "_id: 2,
        "_rev" : "rev",
        "_deleted" : true,
        "type" : "cd"
    }
  ]
}'

This deletes the document while preserving the type information for ES. You can extend this technique to store more data in deleted documents but be aware of the disk space usage.

Indexing parent/child documents

If you need to index relational documents using the parent/child feature, you could do it using a script filter.

For example, let's say you have two types of document in CouchDB: Regions and Campuses.

// Region 1
{
    "type": "region",
    "name": "bretagne"
}
// Campus 2
{
    "type": "campus",
    "name": "enib",
    "parent_id": "1"
}

You can use the following mapping for campus:

{
    "campus" : {
        "_parent" : {
            "type" : "region"
        }
    }
}

And the launch the river with the following script:

{
    "type": "couchdb",
    "couchdb": {
        "script": "ctx._type = ctx.doc.type; if (ctx._type == 'campus') { ctx._parent = ctx.doc.parent_id; }"
    }
}

Removing fields using a script

You can remove fields using a script like this:

{
    "type": "couchdb",
    "couchdb": {
        "script": "var oblitertron = function(x) { var things = [\"foo\"]; var toberemoved = new java.util.ArrayList(); foreach (i : x.keySet()) { if(things.indexOf(i) == -1) { toberemoved.add(i); } } foreach (i : toberemoved) { x.remove(i); } return x; }; ctx.doc = oblitertron(ctx.doc);"
    }
}

A more readable version of the script (with comments) is:

var oblitertron = function (x) {
    // List of fields we want to keep. Others will be removed, such as _id, _rev...
    var things = ["foo"];
    var toberemoved = new java.util.ArrayList();
    foreach(i : x.keySet()) {
        if (things.indexOf(i) == -1) {
            // If we find a field to be removed, we store its name in an array
            toberemoved.add(i);
        }
    }
    // We remove useless fields
    foreach(i : toberemoved) {
        x.remove(i);
    }
    // We return the new document which will be indexed.
    return x;
};
ctx.doc = oblitertron(ctx.doc);

Tests

To run couchdb integration tests, you need to have couchdb running on localhost using default 5984 port. Then you can run tests using tests.couchdb option:

mvn clean test -Dtests.couchdb=true

License

This software is licensed under the Apache 2 license, quoted below.

Copyright 2009-2014 Elasticsearch <http://www.elasticsearch.org>

Licensed under the Apache License, Version 2.0 (the "License"); you may not
use this file except in compliance with the License. You may obtain a copy of
the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
License for the specific language governing permissions and limitations under
the License.
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