An Introduction to Elasticsearch for Beginners

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Elasticsearch

Amir Sedighi

Twitter: @amirsedighi

Blog: http://hexican.com

Email: sedighi@gmail.com

Oct 2014

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References

● http://elasticsearch.org/

● https://www.found.no/foundation/elasticsearch-in-production/

● https://www.found.no/foundation/sizing-elasticsearch/

● https://www.found.no/foundation/elasticsearch-as-nosql/

● https://www.found.no/foundation/elasticsearch-from-the-bottom-up/

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● Thanks to Alex Brasetvik (@alexbrasetvik) from @foundsays, for the slides.

● Thanks to Leslie Hawthorn (@lhawthorn) from @elasticsearch, for the stickers.

Powered by Lucene, Search Stuffs

● 1999 Doug Cutting

● 2003 Doug Cutting

● 2004 Yonik Seeley

● 2010 Shay Banon

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● Full-Text Search Library.● Free & Open-Source● Features:

– Indexes & Analyzes Data

– Tokenizing

– Filtering

– Wildcards

– Aggregation

– Sorting

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● Free and Open-Source

● Java (Cross-platform)

● Real-Time Analytical Search Engine

● Distributed

● Highly Available

● RESTful

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Shard

Inverted Index

One Index Per a Day

A Partial Query

The filtered Query Graph

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Question

● Can ES be used as a "NoSQL"-database?

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Production and Deployment

● Keeping End-users Happy.

● Tracking Quality of Service and Healthy.

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Agenda

● Memory (Performance and Reliability)

● Security

● Networking (Reliability)

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Memory

● Search engines have a great appetite for memory!

– Caches, caches, caches

● Field and filter caches

● Index building

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Comparison

● RDBMSs are built to store. They Put good things in memory, and will flush to disk when there is no memory.

– Slower but working.

– Timeout is a client matter.

● Search-Engines are built for speed.

– Fast running or not running.

– Assumption: You've provided enough memory.

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Question

● What if you don't provide them enough memory?

Question

● What if you don't provide them enough memory?

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Out Of Memory

● In the best case:

– Your Indexing or Search Request simply failed.

● More:

– Cluster state corrupted.

– Crashed Netty.

● Just don't end up there in your production cluster.

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Warning Signs

● ES provides lots of end-points to give you insights into it.

– Resource Usage● Cache Sizes● Heap Space

● There are Monitoring Tools.

– Profile your queries and optimize them.

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Marvel

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Try it on the Cloud by http://found.no

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BigDesk

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Paramedic

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Memory Constraints

● Large heaps are expensive to garbage collect.

– JVM can no longer user pointer compression if heap goes beyond 32GB.

– Keep heap < 32GB

● Single Machine with Huge amount of Memory/SSD.

– Multiple nodes on super-fast machine with SSD and big amount of RAM. (Note: Replicas, SPF)

● Scale-Out

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Security

● Everyone is most welcome.

● Auth(z) things aren't ES business.

– You are the gatekeeper

● Upon the role, limit the user requests applying filters.

– Out of memory is a critical issue. (Attacks)

– Unfiltered or unnecessary queries are pretty memory consuming.

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Security Shield is coming soon

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Networking

● ES works great, on a single node.

● ES is impressively easy to use for being a distributed system.

● ES Supports lots of different network topologies.

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Networking

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Networking

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Networking in a Log Manager

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Suggestions

● Have enough memory to keep your nodes reliable.

● Have majority of nodes.

● Favor filters over matching queries.

● Have an eye on the cluster (Health).

● Don't let user to run faceted queries or reduce the frequency.

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Questions?