- Elasticsearch 5.x Cookbook Third Edition
- Credits
- About the Author
- About the Reviewer
- www.PacktPub.com
- Customer Feedback
- Dedication
- Preface
- 1. Getting Started
- 2. Downloading and Setup
- Introduction
- Downloading and installing Elasticsearch
- Setting up networking
- Setting up a node
- Setting up for Linux systems
- Setting up different node types
- Setting up a client node
- Setting up an ingestion node
- Installing plugins in Elasticsearch
- Installing plugins manually
- Removing a plugin
- Changing logging settings
- Setting up a node via Docker
- 3. Managing Mappings
- Introduction
- Using explicit mapping creation
- Mapping base types
- Mapping arrays
- Mapping an object
- Mapping a document
- Using dynamic templates in document mapping
- Managing nested objects
- Managing child document
- Adding a field with multiple mapping
- Mapping a GeoPoint field
- Mapping a GeoShape field
- Mapping an IP field
- Mapping an attachment field
- Adding metadata to a mapping
- Specifying a different analyzer
- Mapping a completion field
- 4. Basic Operations
- Introduction
- Creating an index
- Deleting an index
- Opening/closing an index
- Putting a mapping in an index
- Getting a mapping
- Reindexing an index
- See also
- Refreshing an index
- Flushing an index
- ForceMerge an index
- Shrinking an index
- Checking if an index or type exists
- Managing index settings
- Using index aliases
- Rollover an index
- Indexing a document
- Getting a document
- Deleting a document
- Updating a document
- Speeding up atomic operations (bulk operations)
- Speeding up GET operations (multi GET)
- 5. Search
- Introduction
- Executing a search
- Sorting results
- Highlighting results
- Executing a scrolling query
- Using the search_after functionality
- Returning inner hits in results
- Suggesting a correct query
- Counting matched results
- Explaining a query
- Query profiling
- Deleting by query
- Updating by query
- Matching all the documents
- Using a boolean query
- 6. Text and Numeric Queries
- Introduction
- Using a term query
- Using a terms query
- Using a prefix query
- Using a wildcard query
- Using a regexp query
- Using span queries
- Using a match query
- Using a query string query
- Using a simple query string query
- Using the range query
- The common terms query
- Using IDs query
- Using the function score query
- Using the exists query
- Using the template query
- 7. Relationships and Geo Queries
- 8. Aggregations
- Introduction
- Executing an aggregation
- Executing stats aggregations
- Executing terms aggregation
- Executing significant terms aggregation
- Executing range aggregations
- Executing histogram aggregations
- Executing date histogram aggregations
- Executing filter aggregations
- Executing filters aggregations
- Executing global aggregations
- Executing geo distance aggregations
- Executing children aggregations
- Executing nested aggregations
- Executing top hit aggregations
- Executing a matrix stats aggregation
- Executing geo bounds aggregations
- Executing geo centroid aggregations
- 9. Scripting
- 10. Managing Clusters and Nodes
- 11. Backup and Restore
- 12. User Interfaces
- 13. Ingest
- 14. Java Integration
- Introduction
- Creating a standard Java HTTP client
- Creating an HTTP Elasticsearch client
- Creating a native client
- Managing indices with the native client
- Managing mappings
- Managing documents
- Managing bulk actions
- Building a query
- Executing a standard search
- Executing a search with aggregations
- Executing a scroll search
- 15. Scala Integration
- 16. Python Integration
- 17. Plugin Development
- 18. Big Data Integration
Elasticsearch allows the user to control the state of the searcher using forced refresh on an index. If not forced, the newly indexed document will be only searchable after a fixed time interval (usually one second).
You need an up-and-running Elasticsearch installation, as used in the Downloading and installing Elasticsearch recipe in Chapter 2, Downloading and Setup.
To execute curl via the command line, you need to install curl for your operative system.
To correctly execute the following commands, use the index created in the Creating an index recipe.
The HTTP method used for both operations is POST. The URL formats for refreshing an index, are:
http://<server>/<index_name(s)>/_refresh
The URL formats, for refreshing all the indices in a cluster, are:
http://<server>/_refresh
For refreshing an index, we will perform the following steps:
- If we consider the type order of the previous chapter, the call will be:
curl -XPOST 'http://localhost:9200/myindex/_refresh' - The result returned by Elasticsearch should be as follows:
{"_shards":{"total":4,"successful":2,"failed":0}}
Near Real-Time (NRT) capabilities are automatically managed by Elasticsearch, which automatically refreshes the indices every second if data is changed in them.
To force a refresh before the internal Elasticsearch interval, you can call the refresh API on one or more indices (more indices are comma separated) or on all the indices.
Elasticsearch doesn't refresh the state of an index at every inserted document as to prevent poor performance due to the excessive I/O required in closing and reopening file descriptors.
Generally, the best time to call the refresh is after having indexed a lot of data to be sure that your records are searchable instantly. It's also possible to force a refresh during a document indexing, adding refresh=true as a query parameter. For example:
curl -XPOST 'http://localhost:9200/myindex/order/2qLrAfPVQvCRMe7Ku8r0Tw? refresh=true' -d '{ "id" : "1234", "date" : "2013-06-07T12:14:54", "customer_id" : "customer1", "sent" : true, "in_stock_items" : 0, "items":[ {"name":"item1", "quantity":3, "vat":20.0}, {"name":"item2", "quantity":2, "vat":20.0}, {"name":"item3", "quantity":1, "vat":10.0} ] }'
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