- 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 is natively designed for the cloud, so when you need to release a production environment with a huge number of records and you need high availability and good performances, you need to aggregate more nodes in a cluster.
Elasticsearch allows defining different type of nodes to balance and improve overall performances.
You need a working Elasticsearch installation as we described in the Downloading and installing Elasticsearch recipe and a simple text editor to change the configuration files.
For advance, set up a cluster. There are some parameters that must be configured to define different node types.
These parameters are in config/elasticsearch.yml file and they can be set with the following steps:
- Set up whether the node can be master or not:
node.master: true
- Set up whether a node must contain data or not:
node.data: true
The node.master parameter defines that the node can become master for the cloud. The default value for this parameter is true.
A master node is an arbiter for the cloud: it takes decisions about shard management, it keeps the cluster status, and it's the main controller of every index action. If your master nodes are on overload, all the clusters will have penalty performances.
The optimum number of master nodes is given by the following equation:
The node.data allows you to store data in the node. The default value for this parameter is true. This node will be a worker that index and search data.
By mixing these two parameters, it's possible to have different node types as shown in the following table:
|
node.master |
node.data |
Node description |
|
|
|
This is the default node. It can be the master, which contains data. |
|
|
|
This node never becomes a master node, it only holds data. It can be defined as a workhorse of your cluster. |
|
|
|
This node only serves as a master: to not store any data and to have free resources. This will be the coordinator of your cluster. |
|
|
|
This node acts as a search load balancer (fetching data from nodes, aggregating results, and so on). |
The more frequently used node type is the first one, but if you have a very big cluster or special needs, you can differentiate the scopes of your nodes to better serve searches and aggregations.
-
No Comment