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You're reading from  Learning Elasticsearch

Product typeBook
Published inJun 2017
PublisherPackt
ISBN-139781787128453
Edition1st Edition
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Author (1)
Abhishek Andhavarapu
Abhishek Andhavarapu
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Abhishek Andhavarapu

Abhishek Andhavarapu is a software engineer at eBay who enjoys working on highly scalable distributed systems. He has a master's degree in Distributed Computing and has worked on multiple enterprise Elasticsearch applications, which are currently serving hundreds of millions of requests per day. He began his journey with Elasticsearch in 2012 to build an analytics engine to power dashboards and quickly realized that Elasticsearch is like nothing out there for search and analytics. He has been a strong advocate since then and wrote this book to share the practical knowledge he gained along the way.
Read more about Abhishek Andhavarapu

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Shrink API

Shrink API is used to shrink an existing index into a new index with a fewer number of shards. If the data in the index is no longer changing, the index can be optimized for search and aggregation by reducing the number of shards. The number of shards in the destination index must be a factor of the original index. For example, an index with 6 primary shards can be shrunk into 3, 2, or 1 shards. When working with time-sensitive data, such as logs, data is only indexed into the current indexes and older indexes are mostly read only. Shrink API doesn't re-index the document; it simply relinks the index segments to the new index.

To shrink an index, the index should be marked as read-only, and either a primary or a replica of all the shards of the index should be moved to one node. We can force the allocation of the shards to one node and mark it as read only as shown...

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Learning Elasticsearch
Published in: Jun 2017Publisher: PacktISBN-13: 9781787128453

Author (1)

author image
Abhishek Andhavarapu

Abhishek Andhavarapu is a software engineer at eBay who enjoys working on highly scalable distributed systems. He has a master's degree in Distributed Computing and has worked on multiple enterprise Elasticsearch applications, which are currently serving hundreds of millions of requests per day. He began his journey with Elasticsearch in 2012 to build an analytics engine to power dashboards and quickly realized that Elasticsearch is like nothing out there for search and analytics. He has been a strong advocate since then and wrote this book to share the practical knowledge he gained along the way.
Read more about Abhishek Andhavarapu