Elasticsearch for Developers with Itamar Syn-Hershko

Topics covered at ELASTICSEARCH-DEV-01-03
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Are you looking for ways to gather insights from the data and logs your system emits? Would you like to join companies like Twitter and LinkedIn in providing your own tailor made search that will enable your users to drill-down and auto-complete features? How about creating shiny dashboards to visualize your system and the behavior of the data you gather? In this intensive 3-day workshop on the leading open-source product Elasticsearch and it's related technology stack you will learn both the basics of full-text search and information retrieval and how to unleash the power of the inverted index, using the powerful ELK stack: Elasticsearch, Logstash and Kibana. Then go on to learn how to monitor and maintain a stable Elasticsearch cluster in production.

Join the Big Data Boutique's Itamar Syn Hershko, who will guide you through hands-on exercises, lectures and discussion of real-world challenges, through which you will be able to achieve a better user experience by incorporating your own search engine in your products. You will also learn how to use the ELK stack to monitor your data real-time, to create live dashboards and to visualize your data.

The second part of the course will explore the various parts that make up a cluster, how it operates, and many do's and don'ts learned by experience over the years.

The goal of this course is to provide experienced developers with all the tools to succeed with integrating Elasticsearch into any type of project, and enable them to maintain a stable cluster regardless of the load put on it.

Learn how to:

  • Use Elasticsearch for full-text search purposes, and query it for other usecases as well
  • Define and maintain Elasticsearch indexes, and index your data into them
  • Perform aggregation queries to drill-down into time-series data and other types of data
  • Understand where Elasticsearch shines and how to use it correctly
  • Develop more advanced skills including:
    • Performance, sizing, scaling out and multi-tenancy
    • Designing the right cluster topology
    • How to monitor the cluster health
    • Understand the various configurations behind the cluster
    • Maintenance and troubleshooting
    • Integration with clouds (AWS, GCP, Azure)
    • Security

About the Author

Itamar Syn-Hershko

An Elasticsearch Consulting Partner, Apache Lucene.NET committer, PMC member and a Microsoft MVP, Itamar is a recognized expert on Architecture, Search and BigData technologies.


Part One

1: Starting with some basics

  • 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

2: The Analysis Chain and Index Mappings

  • 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

3: The Search API

  • 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

4: Elasticsearch must-knows

  • 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

5: The aggregation framework, Logstash, Beats and Kibana

  • Real-time data analysis and reporting
  • The Aggregations Framework: Metric and Bucket aggregations
  • Pipeline aggregations
  • Various powerful aggregations tricks
  • Using Kibana as a powerful Web UI on top of the aggregations framework
  • Timelion
  • Logstash and Beats

Part Two

1: Elasticsearch under the hood

  • Lucene indexes, shards and replicas
  • The inverted index structure
  • FieldData, DocValues and TermVectors
  • Indexing, durability guarantees and it's effects on search

2: Scaling out

  • Elasticsearch Nodes and their roles
  • What it means to scale out
  • The Cluster State
  • Routing
  • Distributed search execution and search types
  • Shard allocation control
  • Tribe nodes
  • Installation and security
  • Working with cloud environments
  • Designing the cluster topology

3: Deployment, Installation and Security

  • Installation, cluster configurations, and gotchas
  • Deploying on the cloud
  • Pre-flight checklist
  • Security
  • Performing upgrades
  • Configurations and cluster state during normal operation
  • Snapshot and restore

4: Monitoring

  • What to monitor?
  • Elasticsearch's configurations and metrics
  • Monitoring the cluster health, and knowing when to react
  • Tweaking configuraitons without risking cluster stability
  • Hard and soft limits
  • Caches and cache invalidation

5: Data ingestion architecture

  • What you should use Elasticsearch for
  • Optimal shard size
  • Index Templates and Aliases
  • Index management patterms
  • Logstash, Beats and Ingest Nodes
  • Document versioning and syncing with external data sources




Developers attending this course should have 3 years of experience or more. Platform doesn't matter as most of the course is hands on using the REST API using dedicated tools (Sense chrome plugin or via Kibana).

Bring your own hardware

In order to participate in this course, you are required to bring your own laptop.