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Retrieving a Documentedit
A document can be retrieved from a primary shard or from any of its replicas, as shown in Figure 10, “Retrieving a single document”.

Here is the sequence of steps to retrieve a document from either a primary or replica shard:
-
The client sends a get request to
Node 1
. -
The node uses the document’s
_id
to determine that the document belongs to shard0
. Copies of shard0
exist on all three nodes. On this occasion, it forwards the request toNode 2
. -
Node 2
returns the document toNode 1
, which returns the document to the client.
For read requests, the coordinating node will choose a different shard copy on every request in order to balance the load; it round-robins through all shard copies.
It is possible that, while a document is being indexed, the document will already be present on the primary shard but not yet copied to the replica shards. In this case, a replica might report that the document doesn’t exist, while the primary would have returned the document successfully. Once the indexing request has returned success to the user, the document will be available on the primary and all replica shards.
- 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