WARNING: The 2.x versions of Elasticsearch have passed their EOL dates. If you are running a 2.x version, we strongly advise you to upgrade.
This documentation is no longer maintained and may be removed. For the latest information, see the current Elasticsearch documentation.
Installing the ICU Plug-inedit
The ICU analysis
plug-in for Elasticsearch uses the International Components for Unicode
(ICU) libraries (see site.project.org) to
provide a rich set of tools for dealing with Unicode. These include the
icu_tokenizer, which is particularly useful for Asian languages, and a number
of token filters that are essential for correct matching and sorting in all
languages other than English.
The ICU plug-in is an essential tool for dealing with languages other than English, and it is highly recommended that you install and use it. Unfortunately, because it is based on the external ICU libraries, different versions of the ICU plug-in may not be compatible with previous versions. When upgrading, you may need to reindex your data.
To install the plug-in, first shut down your Elasticsearch node and then run the following command from the Elasticsearch home directory:
|
The current |
Once installed, restart Elasticsearch, and you should see a line similar to the following in the startup logs:
[INFO][plugins] [Mysterio] loaded [marvel, analysis-icu], sites [marvel]
If you are running a cluster with multiple nodes, you will need to install the plug-in on every node in the cluster.
- Elasticsearch - The Definitive Guide:
- Foreword
- Preface
- Getting Started
- You Know, for Search…
- Installing and Running Elasticsearch
- Talking to Elasticsearch
- Document Oriented
- Finding Your Feet
- Indexing Employee Documents
- Retrieving a Document
- Search Lite
- Search with Query DSL
- More-Complicated Searches
- Full-Text Search
- Phrase Search
- Highlighting Our Searches
- Analytics
- Tutorial Conclusion
- Distributed Nature
- Next Steps
- Life Inside a Cluster
- Data In, Data Out
- What Is a Document?
- Document Metadata
- Indexing a Document
- Retrieving a Document
- Checking Whether a Document Exists
- Updating a Whole Document
- Creating a New Document
- Deleting a Document
- Dealing with Conflicts
- Optimistic Concurrency Control
- Partial Updates to Documents
- Retrieving Multiple Documents
- Cheaper in Bulk
- Distributed Document Store
- Searching—The Basic Tools
- Mapping and Analysis
- Full-Body Search
- Sorting and Relevance
- Distributed Search Execution
- Index Management
- Inside a Shard
- You Know, for Search…
- Search in Depth
- Structured Search
- Full-Text Search
- Multifield Search
- Proximity Matching
- Partial Matching
- Controlling Relevance
- Theory Behind Relevance Scoring
- Lucene’s Practical Scoring Function
- Query-Time Boosting
- Manipulating Relevance with Query Structure
- Not Quite Not
- Ignoring TF/IDF
- function_score Query
- Boosting by Popularity
- Boosting Filtered Subsets
- Random Scoring
- The Closer, The Better
- Understanding the price Clause
- Scoring with Scripts
- Pluggable Similarity Algorithms
- Changing Similarities
- Relevance Tuning Is the Last 10%
- Dealing with Human Language
- Aggregations
- Geolocation
- Modeling Your Data
- Administration, Monitoring, and Deployment