Elasticsearch 5.0

Nov 11, 2016Download as PPTX, PDF4 likes2,103 views

Matias Cascallares

What's new in Elasticsearch 5.0? Take a look at all the new cool features we introduced in version 5.

• Made in Argentina, living in Singapore
• Java / Python / NodeJS
• Working with/in open source for the last 8 years
• Using Elasticsearch since 2014, working for Elastic since 2015
• Meme lover
> whoami

8
Store, Index & Analyze
• Resilient; designed for
scale-out
• High availability;
multitenancy
• Structured & unstructured
data
Distributed
& Scalable
Developer
Friendly
Search &
Analytics
• Schemaless
• Native JSON
• Client libraries
• Apache Lucene
• Real-time
• Full-text search
• Aggregations
• Geospatial
• Multilingual

• Lower memory usage & improved cluster stability
(new keyword type)
• Better scoring, faster, reduced hardware demand
(Okapi BM25)
• IPv6 type support
Update To Lucene 6

• Half the disk space
• Twice as fast to ingest
• 25% faster to search
• For numeric and geospatial fields only
• Scaled floats
• Technically a BKD Tree implementation
Lucene Demensional Fields

• Aggregation and suggestion results are
cached on shard level for instant returns
after the first query.
• Combined with a new query rewrite,
typical Kibana dashboards that use “last
X days” type of queries will improve
dramatically.
Shard Request Cache

Rollover API
• Indices not based on time, but on size of the data.
• Even if your data sizes are not consistent per day, Elasticsearch will use
constant index/shard sizes.
• Set up rules around automatic rollover to a new index, with aliases.

Shrink API
• Reduce resources on immutable data
• Easily reduce the number of shards to free up resources
• Indices can be shrunk to a factor of its original number of shards

• Low-level client
• Allows communication through HTTP/S
• Sync and Async semantics
• Connection handling
• Node discovery (sniffer module)
Java REST Client

• Define processing pipelines right in the Elasticsearch cluster.
• Depending on use case, can simplify the architecture
• Has Processors for the most common actions.
• Combine it with Logstash when needed for power & flexibility.
Ingest Node

Bootstrap Checks
• Detects if it’s running in production or development mode
• When running in production, it will now refuse to start under certain conditions
that could seriously impact performance, stability, or data integrity
‒ Heap size (initial vs max)
‒ Memory lock (mlockall)
‒ Virtual memory size
‒ File descriptors
‒ Threads
‒ JVM in server mode

More Goodies…
• Dots in field names was supported in 1.x, and was removed in 2.x. 5.0
support dots in field names again!

More Goodies…
• New lock method increases small document indexing up to 15-20%
• New fsync method for increased ingestion speed
• refresh=[true|wait_for] for index, update, delete and bulk APIs
• Migration Helper
‒ Cluster checkup before upgrading
‒ Reindex helper for 1.x indices
‒ Deprecation logging

Version Compatibility
IDX_v1x IDX_v2x IDX_v5x
ES 1.X
ES 2.X
ES 5.X

Website: www.elastic.co
Products: https://www.elastic.co/products
Forums: https://discuss.elastic.co/
Community: https://www.elastic.co/community/meetups
Twitter: @elastic
Thank You.

Elasticsearch is a distributed, open source search and analytics engine built on Apache Lucene. It allows storing and searching of documents of any schema in JSON format. Documents are organized into indexes which can have multiple shards and replicas for scalability and high availability. Elasticsearch provides a RESTful API and can be easily extended with plugins. It is widely used for full-text search, structured search, analytics and more in applications requiring real-time search and analytics of large volumes of data.

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