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Intro to Elasticsearch

Get started with Elasticsearch

If you’re just getting started, after taking this comprehensive 2-day session (two 4-hour sessions), you will understand all core Elasticsearch concepts – data, master and client nodes and their differences, sharding, replication, mapping, search relevance scoring, etc.

Your trainer is an active Elasticsearch consultant who worked with clients from 20+ different industries and the author of Elasticsearch in Action.

Here are some problems Radu Gheorghe, your Elasticsearch trainer, solved for Sematext clients recently:

  • Improved search relevancy using Learning to Rank
  • Optimized multiple petabyte-scale clusters. Some up to 400 nodes.
  • Designed Elasticsearch index and cluster architecture for dozens of clients
  • Optimized log ingestion pipelines to parse and enrich 100K+ events/second
  • Helped clients reduce production Elasticsearch and ingestion pipeline costs by as much as 10x

A word from Radu Gheorghe

“Attendees come in highly motivated, making the class feel more “alive” than I expected. They constantly look for takeaways to improve their setup, from tweaking a boost to changing the sharding strategy. Their use-cases are very diverse, too, so we end up covering a lot of material.

Radu Gheorghe Sematext Elasticsearch Training Instructor

8-hour online class available upon request

Looking for an extended knowledge-based introduction to Elasticsearch training? You’ve come to the right place.

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Why attend?

  • Small, interactive, instructor-led classes
  • Lots of hands-on exercises
  • Customized learning experience
  • More flexible – no need to travel
  • Certificate of Completion included

Who should attend?

This Elasticsearch online course is designed for technical attendees with any knowledge level.

No prior Elasticsearch experience or knowledge is required. Experience with Linux is not a must, but basic familiarity with running shell commands (e.g., using curl command) will make the course more enjoyable.

What attendees say

Sematext was an ideal training partner for Parse.ly. We had just recently adopted Elasticsearch on a new project, and they gave us two days of solid training that was tailored to our team’s needs. The material was built atop strong foundations and moved quickly into advanced areas around querying, Lucene internals, and cluster performance. It was clear that it was all informed by real-world experience operating these systems at scale.

Andrew Montalenti CTO/Founder – Parse.ly

Course Outline

Basic flow of data in Elasticsearch
  • What is Elasticsearch and typical use-cases
  • Shards and replicas; packaging
  • Installation; configuration files
  • Indexing; what is an index, type and ID
  • Mappings; stored and indexed fields; _source and _all
  • Analysis basics
  • Realtime get
  • Search; how searches are distributed to shards
  • Ranking by TF/IDF and BM25
  • Aggregations and doc values introduction
  • Updates; versioning
  • Deletes; introduction to Lucene segment merges
  • Lab
    • CRUD operations
    • Query and filter
    • Pagination
Controlling how data is indexed and stored
  • Mappings and mapping types
  • Multi-field definitions
  • Default mappings; dynamic mappings
  • Texts, keywords, integers and other core types
  • Date formats
  • Predefined fields; when to store fields separately vs using _source
  • Analyzers; using the Analyze API
  • Char filters
  • Tokenizers: standard vs whitespace
  • Token filters: lowercase, stopwords, synonyms, ngrams and shingles
  • Lab
    • Exact match vs full-text search
    • Using the asciifolding token filter for better internationalization
    • Using language analyzers to support stemming
Searching through your data
  • Selecting fields, source filtering and fielddata fields
  • Sorting and pagination
  • Search basics: term, range and bool queries
  • Enable caching through the filter context
  • Match query: configuring the analyzer, operator, common terms and fuzziness
  • Query string and simple query string queries
  • Lab
    • Using various ways of selecting fields
    • Configure sorting and pagination
    • Using a bool query to combine different match, range and term queries
    • Boosting exact matches above stemmed ones
Aggregations
  • Relationships between queries and aggregations; post filter, global aggregations
  • General optimizations: avoid script fields, set result size to 0 to cache
  • Metrics aggregations: stats, cardinality, percentiles
  • Why terms, cardinality and percentiles are approximate
  • Multi-bucket aggregations: terms, ranges and histograms
  • Single-bucket aggregations and nesting; how nesting works
  • Lab
    • Configure sizes of results, per-shard and overall buckets
    • Computing the cardinality of a field
    • Sorting buckets by results of sub-aggregations
    • Optimizing terms queries by configuring collect mode
    • Nest the sum and histogram aggregations

Main Topics

  • Elasticsearch Basic Concepts
  • Elasticsearch Strengths and Weaknesses
  • Elasticsearch CRUD Operations
  • Field types and Predefined Fields
  • Using and Customizing Analyzers
  • Types of Queries and Aggregations
  • Shards, Replicas and Clustering

Elasticsearch Training

Course key takeaways

After taking this course you will:

  • Understand all core Elasticsearch concepts – data, master, and client nodes and their differences, sharding, replication, mapping, search relevance scores, etc.
  • Be able to index data into Elasticsearch and retrieve it using search and realtime get APIs
  • Have a solid grasp of the underlying query parsing, analysis, tokenization, and various types of queries
  • Learn about a number of different types of Elasticsearch aggregations

Things to remember

Participants must use their own computer with OSX, Linux, or Windows, with a recent version of Java installed.

Participants should be comfortable using a terminal/command line. Sematext provides:
  • A digital copy of the training material
  • A VM with all configs, scripts, exercises, etc.

Want to master your Elasticsearch use case faster?

Pick from a wide range of short (2h), use case focused classes to fit your exact needs

  • Online
  • 2-hours
  • Use-case focused
  • Instructor-led

Elasticsearch Fundamentals

Understand how Elasticsearch works and get started with setting it up for either search or log aggregation.

Read more

Kibana and Logstash Fundamentals

Get started with Logstash and Kibana, so you can build an ELK stack: from parsing logs to building dashboards.

Read more

Elasticsearch Scaling 101

Learn about how nodes and shards work, so you can scale your Elasticsearch cluster from PoC to as much as you hardware can hold.

Read more

Elasticsearch Scaling 202

Learn index and cluster architectures that make clusters scale, from time- and size-based indices, to cross-cluster search.

Read more

Elasticsearch Tuning 101

From caches and refreshes to routing, learn about the most important knobs that influence both indexing and search performance.

Read more

Elasticsearch Tuning 202

From hardware choices, to garbage collection, merge policy and thread pool tuning – learn how to squeeze even more performance from your cluster.

Read more

Monitoring Elasticsearch

Bridge the gap between having proper Elasticsearch monitoring in place and understanding how to diagnose and troubleshoot the cluster.

Read more

Administering Elasticsearch

Fully understand Elasticsearch’s management capabilities: from pre-configuring index settings and mappings to how to safely perform upgrades.

Read more

Need On-Site or Remote Training

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