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Learning Elasticsearch

You're reading from   Learning Elasticsearch Structured and unstructured data using distributed real-time search and analytics

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787128453
Length 404 pages
Edition 1st Edition
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Author (1):
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Abhishek Andhavarapu Abhishek Andhavarapu
Author Profile Icon Abhishek Andhavarapu
Abhishek Andhavarapu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Elasticsearch FREE CHAPTER 2. Setting Up Elasticsearch and Kibana 3. Modeling Your Data and Document Relations 4. Indexing and Updating Your Data 5. Organizing Your Data and Bulk Data Ingestion 6. All About Search 7. More Than a Search Engine (Geofilters, Autocomplete, and More) 8. How to Slice and Dice Your Data Using Aggregations 9. Production and Beyond 10. Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Translog

In the What happens when you index a document section, we discussed that when you index a document, the refresh process creates a new segment. Since writing the segment to the disk on every refresh is very expensive, the segment is only written to in-memory file system cache. When certain conditions are met, a process known as Lucene commit writes all the files (segments) in the memory to a physical disk.

If a node crashes before the files in memory are persisted to the physical disk, the data in the file system cache is lost, and any uncommitted changes are also lost. But Lucene commit is very expensive and cannot be done after every operation. To solve this problem, Elasticsearch introduced transaction log, which is a write-ahead log:

During an index or delete operation, the document is written to both the memory buffer and the transaction log. The index/delete operation...

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