Before you begin reading this guide, we recommend you try running the Elasticsearch Error Check-Up which analyzes 2 JSON files to detect many configuration errors.
Briefly, this error message indicates that a script filter is being used in a query, but the corresponding script is missing. Script filters allow you to customize the scoring of search results in Elasticsearch using a custom script. To resolve this error, ensure that a valid script is provided when defining the script filter.
To easily locate the root cause and resolve this issue try AutoOps for Elasticsearch & OpenSearch. It diagnoses problems by analyzing hundreds of metrics collected by a lightweight agent and offers guidance for resolving them.
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This guide will help you check for common problems that cause the log ” script must be provided with a script filter ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: filter, query and index.
Overview
A filter in Elasticsearch is all about applying some conditions inside the query that are used to narrow down the matching result set.
What it is used for
When a query is executed, Elasticsearch by default calculates the relevance score of the matching documents. But in some conditions it does not require scores to be calculated, for instance if a document falls in the range of two given timestamps. For all these Yes/No criteria, a filter clause is used.
Examples
Return all the results of a given index that falls between a date range:
GET my_index/_search
{
"query": {
"bool": {
"filter": {
"range": {
"created_at": {
"gte": "2020-01-01",
"lte": "2020-01-10"
}
}
}
}
}
}Notes
- Queries are used to find out how relevant a document is to a particular query by calculating a score for each document, whereas filters are used to match certain criteria and are cacheable to enable faster execution.
- Filters do not contribute to scoring and thus are faster to execute.
- There are major changes introduced in Elasticsearch version 2.x onward related to how query and filters are written and performed internally.
Common problems
- The most common problem with filters is incorrect use inside the query. If filters are not used correctly, query performance can be significantly affected. So filters must be used wherever there is scope of not calculating the score.
- Another problem often arises when using date range filters, if “now” is used to represent the current time. It has to be noted that “now” is continuously changing the timestamp and thus Elasticsearch cannot use caching of the response since the data set will keep changing.
Overview
In Elasticsearch, an index (plural: indices) contains a schema and can have one or more shards and replicas. An Elasticsearch index is divided into shards and each shard is an instance of a Lucene index.
Indices are used to store the documents in dedicated data structures corresponding to the data type of fields. For example, text fields are stored inside an inverted index whereas numeric and geo fields are stored inside BKD trees.
Examples
Create index
The following example is based on Elasticsearch version 5.x onwards. An index with two shards, each having one replica will be created with the name test_index1
PUT /test_index1?pretty
{
"settings" : {
"number_of_shards" : 2,
"number_of_replicas" : 1
},
"mappings" : {
"properties" : {
"tags" : { "type" : "keyword" },
"updated_at" : { "type" : "date" }
}
}
}List indices
All the index names and their basic information can be retrieved using the following command:
GET _cat/indices?v
Index a document
Let’s add a document in the index with the command below:
PUT test_index1/_doc/1
{
"tags": [
"opster",
"elasticsearch"
],
"date": "01-01-2020"
}Query an index
GET test_index1/_search
{
"query": {
"match_all": {}
}
}Query multiple indices
It is possible to search multiple indices with a single request. If it is a raw HTTP request, index names should be sent in comma-separated format, as shown in the example below, and in the case of a query via a programming language client such as python or Java, index names are to be sent in a list format.
GET test_index1,test_index2/_search
Delete indices
DELETE test_index1
Common problems
- It is good practice to define the settings and mapping of an Index wherever possible because if this is not done, Elasticsearch tries to automatically guess the data type of fields at the time of indexing. This automatic process may have disadvantages, such as mapping conflicts, duplicate data and incorrect data types being set in the index. If the fields are not known in advance, it’s better to use dynamic index templates.
- Elasticsearch supports wildcard patterns in Index names, which sometimes aids with querying multiple indices, but can also be very destructive too. For example, It is possible to delete all the indices in a single command using the following commands:
DELETE /*
To disable this, you can add the following lines in the elasticsearch.yml:
action.destructive_requires_name: true
Log Context
Log “script must be provided with a [script] filter”classname is ScriptQueryBuilder.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :
"[script] query does not support an array of scripts. Use a bool query with a clause per script instead.");
}
}
if (script == null) {
throw new ParsingException(parser.getTokenLocation(); "script must be provided with a [script] filter");
}
return new ScriptQueryBuilder(script)
.boost(boost)
.queryName(queryName);
