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Elasticsearch for Developers
Master how to use Elasticsearch for everything from text search to log analysis and anomaly detection in this hands-on 2 day course
2 days
20
Instructor-led, hands-on exercises
Hebrew
Bring your own (installation instructions will be sent prior to course start)
Included
Elasticsearch is today's de-facto standard for centralized logging and real-time analytics for system metrics and business data. What started as a full-text search engine quickly became much, much more than just that.
This intensive 2-day hands-on workshop is designed to teach you Elasticsearch from the ground up. You will start by learning the basics of full-text search and information retrieval and the important Elasticsearch APIs: Document, Indexes, Queries and Aggregations APIs.
Only once you are fluent with the Elasticsearch APIs you can really use this powerful technology to its full potential. Formerly known as ELK, the Elastic Stack has several components (Elasticsearch, Logstash, Kibana, Beats, and several Stack-wide solutions), and you will learn how to make good use of them all.
Objectives
The goal of this course is to provide an experienced developer with all the tools to succeed with integrating Elasticsearch into any type of project. You will learn:
- Using Elasticsearch to add full-text search to any application.
- Define and maintain Elasticsearch indexes, and correct data ingestion using Logstash and Beats.
- Perform aggregation queries to drill-down into your data.
- Use Kibana to investigate live data and create visually appealing dashboards.
- Working with time-series data (logs, IoT, and more).
- Understand where the Elastic Stack shines and how to use it correctly.
Prerequisites
Developers, DevOps and SREs with 3 years of experience or more. Platform agnostic - hands-on exercises are using Kibana end-to-end.
Syllabus
- Basics of Full text search and Information Retrieval
- Overview of the Elastic stack
- Elasticsearch and the REST API
- Using Elasticsearch from your favorite programming language
- Search and the various query types
- Hands-on experience with indexing and searching texts
- The inverted index and full-text search
- Term normalization with Analyzers, Tokenizers and TokenFilters
- Understanding and poking into the analysis chain
- Creating and using a custom analyzer
- Using Index Mappings to control analysis and other index features
- Pagination and Sorting
- Precision and Recall
- Understanding scoring and how it is applied
- Building smart queries that can influence scoring correctly
- Scripting
- Query explanation and profiling
- Results highlighting
- Various power query tools and a lot of good advice
- Document oriented design and why it's crucial to do right with Elasticsearch
- Suggesters
- Record linkage via MoreLikeThis
- Geo-spatial search
- Multi-lingual search
- Anomaly detection methods
- The percolator
- Real-time data analysis and reporting
- The Aggregations Framework: Metric and Bucket aggregations
- Pipeline aggregations
- Various powerful aggregations tricks
- Using Kibana to visualize data
- Elasticsearch Nodes and their roles (data, master, client)
- Replication and sharding
- Cluster topology
- Performance, sizing and scaling out
- Monitoring the cluster health, and knowing when to react
- Logstash, Beats and the Elastic Stack components