原文地址: https://www.elastic.co/guide/en/elasticsearch/guide/current/_partial_updates_to_a_document.html, 版权归 www.elastic.co 所有
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Partial Updates to a Documentedit
The update
API , as shown in Figure 11, “Partial updates to a document”, combines the read and write patterns explained previously.

Figure 11. Partial updates to a document
Here is the sequence of steps used to perform a partial update on a document:
-
The client sends an update request to
Node 1
. -
It forwards the request to
Node 3
, where the primary shard is allocated. -
Node 3
retrieves the document from the primary shard, changes the JSON in the_source
field, and tries to reindex the document on the primary shard. If the document has already been changed by another process, it retries step 3 up toretry_on_conflict
times, before giving up. -
If
Node 3
has managed to update the document successfully, it forwards the new version of the document in parallel to the replica shards onNode 1
andNode 2
to be reindexed. Once all replica shards report success,Node 3
reports success to the coordinating node, which reports success to the client.
The update
API also accepts the routing
, consistency
, and
timeout
parameters that are explained in Creating, Indexing, and Deleting a Document.
- 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
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- Query-Time Boosting
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- Not Quite Not
- Ignoring TF/IDF
- function_score Query
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- 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
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- Modeling Your Data
- Administration, Monitoring, and Deployment