Chapter 7. Scripting

In this chapter, we will cover the following topics:

• Installing additional script plugins

• Sorting using script

• Computing return fields with scripting

• Filtering a search via scripting

• Updating with scripting

Introduction

ElasticSearch has a powerful way to extend its capabilities with custom scripts that can be written in several programming languages. The most common ones are MVEL, JavaScript, and Python.

We already have a taste of the scripting capabilities of ElasticSearch, in the previous chapter, using scripting for facets. In this chapter we will see how it's possible to create custom scoring algorithms, special processed return fields, custom sorting or complex update operations on records.

The scripting concept of ElasticSearch can be seen as an advanced stored procedures system in the NoSQL world; so, for an advanced use of ElasticSearch, it is very important to master it.

Installing additional script plugins

ElasticSearch provides native scripting (a Java code compiled in JAR) and MVEL, but a lot of interesting languages are available, such as JavaScript and Python. These languages must be installed as plugins.

Getting ready

You need a working ElasticSearch cluster.

How to do it...

For installing a JavaScript language support for Elasticsearch, we will perform the following steps:

1. From the command line, simply call the following command:

   bin/plugin --install elasticsearch/elasticsearch-lang-javascript/1.4.0
   

2. It will fire as results:

   -> Installing elasticsearch/elasticsearch-lang-javascript/1.4.0...
   Trying http://download.elasticsearch.org/elasticsearch/elasticsearch-lang-javascript/elasticsearch-lang-javascript-1.4.0.zip...
   Downloading ....DONE
   Installed lang-javascript
   

   If the installation is successful, the output will end with Installed; otherwise, an error is returned.

3. For installing a Python language support for Elasticsearch, just call the following command...

Sorting using script

ElasticSearch provides scripting support for sorting functionality. In real-world applications, there is often a need to modify the score using an algorithm that depends on the context and some external variables. Some common scenarios are as follows:

• Sorting places near a point

• Sorting by most read articles

• Sorting items by custom customer logic

• Sorting items with more revenue

Getting ready

You need a working ElasticSearch cluster and an index populated with the script used for facet processing, available in the online code.

How to do it...

For sorting using scripting, we will perform the following steps:

1. If we want to order our documents by the price field multiplied by a factor parameter (usually VAT), the search will be as shown in the following code:

    curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{
     "query": {
       "match_all": {}
     },
     "sort": {
       "_script" : {
         "script" : "doc[\"price\"].value * factor",
         "type...

Computing return fields with scripting

ElasticSearch allows us to define complex expressions that can be used to return a new calculated field value.

These special fields are called script_fields, and they can be expressed with a script in every available ElasticSearch scripting language.

Getting ready

You need a working ElasticSearch cluster and an index populated with the script used for facet processing, available in the online code.

How to do it...

For computing return fields with scripting, we will perform the following steps:

1. Return the following script fields:

   • "my_calc_field": This concatenates the texts of the "name" and "description" fields

   • "my_calc_field2": This multiplies the "price" value by the "discount" parameter

2. From the command-line, we will execute the following code:

   curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{
     "query": {
       "match_all": {}
     },
     "script_fields" : {
       "my_calc_field" : {
         "script" : "doc[\"name\"...

Filtering a search via scripting

In Chapter 5, Search, Queries, and Filters, we have seen many filters. ElasticSearch scripting allows extending the traditional filter with custom script.

Using scripting to create a custom filter is a convenient way to write scripting rules not provided by Lucene or ElasticSearch and to create business rules not available in query DSL.

Getting ready

You need a working ElasticSearch cluster and an index, populated with the script used for facet processing, available in the online code.

How to do it...

For filtering a search using a scripting, we will perform the following steps:

1. We'll write a search with a filter that filters out a document with an age value less than a parameter value:

    curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{
     "query": {
       "filtered": {
         "filter": {
           "script": {
             "script": "doc[\"age\"].value > param1",
             "params" : {
               "param1" : 80
           ...

Updating with scripting

ElasticSearch allows updating a document in-place.

Updating a document via scripting reduces networking traffic (otherwise, you need to fetch the document, change the field, and send it back) and allows improving performance when you need to process a huge amount of documents.

Getting ready

You need a working ElasticSearch cluster and an index populated with the script used for facet processing, available in the online code.

How to do it...

For updating using a scripting, we will perform the following steps:

1. We'll write an update action that adds a tag value to a list of tags available in the source of a document. It should look as shown in the following code:

    curl -XPOST 'http://127.0.0.1:9200/test-index/test-type/9/_update?&pretty=true' -d '{
       "script" : "ctx._source.tag += tag",
       "params" : {
           "tag" : "cool"
       }
   }'

2. If everything is correct, the result returned by ElasticSearch should be:

   {
     "ok" : true,
     "_index" : "test-index",
     "_type" : "test-type...