1. The reason for the jump of ES5.0 version number
ELK is the acronym for Elasticsearch, Logstash, and Kibana. Now Elastic has added a new open source project member: Beats. Due to the confusion of the current version, the version number of each product is different. Elasticsearch and Logstash are currently 2.3.4; Kibana is 4.5.3; Beats is 1.2.3; the version number is too messy, what version of ES is there? What version of Kibana are you using? Are there compatibility issues?
Therefore, the ES development team intends to unify the version numbers of these products, that is, v5.0, why is it 5.0, because Kibana is 4.x, the next version can only be 5.0, and other products will jump along, Therefore, the ES5.0 version came into being.
2. Features of the new version
The new features have been available for a while. In September of last year, I studied the features of the beta version of the new version. In view of the reasons for the Head plug-in and SQL plug-in, they have not been updated and used in the production environment. Recently, I found that the Head plug-in and SQL plug-in are mature, and the installation method is very different from before. Not the same, so I decided to write an installation record blog
1. Added a Shrink API ---> Prime Factor Shrinking Fragments
I believe everyone knows that the number of shards in the elasticsearch index is fixed, and it cannot be modified after it is set. If you find that there are too many or too few shards, if you want to set the number of shards in Elasticsearch, you can only set it when you create the index. , and the data cannot be modified after it comes in. If you want to modify it, you can only rebuild the index.
Now with the Shrink interface, it can shrink the number of shards to its factor. For example, if you had 15 shards before, you can shrink it into 5 or 3 or 1, then we can imagine it as such In this scenario, in the collection stage where the writing pressure is very high, set enough indexes to make full use of the parallel writing capability of shards. After the indexes are written, they shrink into fewer shards to improve query performance.
2. Added a Rollover API. ---> Automatically create new indexes
Generally, we divide the index by day (the data volume can be further divided), we used to set up a template to automatically generate the index in the program, everyone who has used logstash should remember that there is such a template logstash-[YYYY -MM-DD] template, now es5.0 provides a simpler way: Rollover API
3. New: Reindex --> Index rebuild and migrate data, which can expand shards in disguised form
In addition, with regard to index data, we often rebuild the data before. The data source is in various scenarios, and it is very difficult to rebuild. Then we have to talk about the newly added Reindex interface. Reindex can directly rebuild the data in the Elasticsearch cluster. If When your mapping needs to be rebuilt due to modification, or when the index settings need to be rebuilt, Reindex can be used to facilitate asynchronous reconstruction and support data migration across clusters.
For example, an index created on a daily basis can be periodically rebuilt and merged into a monthly index.
Of course, _source should be enabled in the index.
3. ES Ecosystem Circle
