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:
- Small, interactive, instructor-led classes
- Lots of hands-on exercises
- Customized learning experience
- More flexible – no need to travel
- Certificate of Completion included
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.
- 8-hour online training
- A digital copy of the training material
- Docker Compose files, configs, scripts, etc.
- Certificate of Completion
Next Class: Sept 20-21, 2021 See Upcoming Classes
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.
Not your typical by-the-book training. Radu was engaging and was a great guide in our journey through Elasticsearch.
I had to leave before the last class ended unfortunately. But had I been there I would have given you a mini-speech to tell you how awesome you were! ☺️
Thank you so much for being such a fantastic, patient, and effective instructor throughout this 4-day training. Personally, I appreciated the clarity and expertise in the material and the class.
I also thought the class was meticulously structured over the 4 days, each day not feeling too long, and with the right number of breaks – this made me feel like I had the capacity to learn the things planned for the day without feeling too overwhelmed. Having the course material is great for the team to revisit later.
Overall, we really felt like we learned a lot. To put it in perspective, <name redacted for privacy> (who worked with <name redacted> and <name redacted>) already applied some of the lessons from the training in one of our customer throughput issues today. A big progress for the team. And, I am sure we will continue to apply in the future too – I just want you to know that you have clearly influenced us ☺️
Pick from our 8h online classes, structured to correspond to different roles and Elasticsearch knowledge levels: for beginners to experienced developers or ops who want to learn quickly. Delivery method: Live Online. Time: 09:00 AM – 01:00 PM ET (2 sessions).
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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
- CRUD operations
- Query and filter
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
- 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
- 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
- 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
- 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
- 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
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.
Need On-Site or Remote Training
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