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ElasticSearch Blueprints

You're reading from   ElasticSearch Blueprints A practical project-based guide to generating compelling search solutions using the dynamic and powerful features of Elasticsearch

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Product type Paperback
Published in Jul 2015
Publisher Packt
ISBN-13 9781783984923
Length 192 pages
Edition 1st Edition
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Toc

Table of Contents (10) Chapters Close

Preface 1. Google-like Web Search 2. Building Your Own E-Commerce Solution FREE CHAPTER 3. Relevancy and Scoring 4. Managing Relational Content 5. Analytics Using Elasticsearch 6. Improving the Search Experience 7. Spicing Up a Search Using Geo 8. Handling Time-based Data Index

Closing older indices


As the time progresses, the documents residing in the older indices will be even less utilized to the level that they might not even be accessed. These indices would use our CPU, main memory, and other resources as they reside in the disk in their nodes. This situation is not a healthy one, as we are simply giving away our resources for the unused or unaccessed data. Elasticsearch provides us a provision to manage this situation by letting us "close" old indices.

Closing an index means that the index would still remain in the cluster with no resource except the disk space being used. The advantage of closing an index is that it is much easier to reopen it than restoring the index from a backup.

We can close that index using the close API:

POST / logstash-02-06-2015/_close

As mentioned earlier, the specified index will be stored in the disk, but all the read/write operations would be blocked for it.

In case we want to reopen the index, we can do so using the open API:

POST...
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