Introduction
Searching across multiple indexes in Elasticsearch can be a common requirement in various use cases. In this article, we will discuss the best practices and optimization techniques when performing multi-index searches in Elasticsearch.
Best practices & Optimization Techniques Multi-Index Searches in Elasticsearch
1. Use Wildcards or Aliases for Index Selection
When searching across multiple indexes, you can use wildcards or aliases to target the desired set of indexes. Wildcards allow you to search across indexes with a similar naming pattern, while aliases can be used to group multiple indexes under a single name.
Example using wildcard:
GET /logs-*/_search
{
"query": {
"match": {
"message": "error"
}
}
}Example using alias:
GET /all-logs/_search
{
"query": {
"match": {
"message": "error"
}
}
}2. Limit the Number of Shards
Searching across a large number of shards can impact performance. To optimize your search, try to limit the number of shards involved in the query by reducing the number of indexes or using the `routing` parameter to target specific shards.
3. Use Filtered Aliases
Filtered aliases can help you narrow down the scope of your search by applying a filter to the alias itself. This way, you can avoid searching through irrelevant documents, thus improving search performance.
Example of creating a filtered alias:
PUT /_aliases
{
"actions": [
{
"add": {
"index": "logs-*",
"alias": "error-logs",
"filter": {
"term": {
"level": "error"
}
}
}
}
]
}4. Use the Multi-Search API
The Multi-Search API allows you to execute multiple search requests within a single API call. This can be useful when you need to query multiple indices with different queries or when you want to compare results from different indices. To use the Multi-Search API, you can send a request like this:
POST /_msearch
{"index": "logs-2023-01"}
{"query": {"match": {"message": "error"}}}
{"index": "logs-2023-02"}
{"query": {"match": {"message": "warning"}}}In this example, we execute two search requests: one for the “logs-2023-01” index with a query for “error” messages, and another for the “logs-2023-02” index with a query for “warning” messages. The Multi-Search API returns an array of responses, one for each search request.
5. Optimize Query Performance
When searching across multiple indexes, it’s crucial to optimize your queries for better performance. Some tips include:
– Use `bool` queries with `filter` clauses for non-scoring queries.
– Use source filtering to return only the required fields.
– Use pagination with the `from` and `size` parameters to limit the number of results returned.
6. Leverage Cross-Cluster Search (CCS)
If you have data spread across multiple Elasticsearch clusters, you can use Cross-Cluster Search (CCS) to search across all clusters simultaneously. This feature allows you to perform a single query across multiple remote clusters, simplifying your search process.
Example of CCS search:
GET /cluster1:logs-*,cluster2:logs-*/_search
{
"query": {
"match": {
"message": "error"
}
}
}Conclusion
By following these best practices and optimization techniques, you can improve the performance of your multi-index searches in Elasticsearch and ensure that your queries return relevant results in a timely manner.
