Elastic Certified Engineer Exam V8.1

Define an index in Elasticsearch with aliases, mappings, and settings, then create and delete it, use the alias, and post and search data.

Define and apply an index template that matches a given pattern, set shards and replicas, and compose templates with component templates to automatically apply settings to new indices.

Explore how to define and use a dynamic template to apply field type rules in Elasticsearch mappings, covering dynamic mappings, runtime mappings, and keyword versus ip address handling.

Define an index lifecycle management policy for a time series index and create a matching index template to form a data stream, illustrating hot, warm, cold, and frozen phases.

Define a component template with index settings and an index template that enables a data stream and applies a hot, warm, cold, delete lifecycle policy.

Practice scenario shows configuring an Elastic data stream with a hot-warm-cold-delete ILM policy, a logs component template, and a logs index template, then testing by posting a document.

Learn how to perform asynchronous searches in Elasticsearch by issuing a request, polling with a search ID for completion, and retrieving results while optionally deleting the cached search.

Configure and run two Elasticsearch clusters, set non-default ports, register a remote cluster, and execute a cross-cluster search across multiple indices.

Explore 20 Elasticsearch queries, from simple match to fuzzy and prefix, including range, exists, wildcard, regexp, match phrase, and boolean must/should/must not, using sample ecommerce data.

Learn to write and execute a search query that combines multiple queries and filters using boolean logic, targeting terms or phrases in one or more fields.

Learn to write and execute searches with runtime fields in Elasticsearch, using schema on read and runtime mappings to compute fields on the fly for searches, aggregations, filtering, and sorting.

Explore how to write and execute aggregations and sub-aggregations in Elastic, including sum, average, max, min, count, stats, extended stats, and cardinality across date histogram and bucket analyses.

Learn to write and execute metric and bucket aggregations, including sub aggregations, within the searching data objective of the Elastic Certified Engineer Exam V8.1.

Download the movie data csv from the shared drive, upload it for the Elastic Certified Engineer exam, import with the required name, and follow the slides for timing and naming.

Install or upload the addresses dataset for Elastic Certified Engineer examples by downloading from a shared drive, previewing, and importing with an index name, then verify via get cat indices.

Explore scenario-based questions on nested aggregations and asynchronous search in Elasticsearch, building a week-by-week distance miles average via a date histogram and bucket sorting the results by descending averages.

Explore a scenario-based Elastic Certified Engineer exam problem: group flights by airline, compute the average air time per airline, and identify the maximum average using a max bucket sibling aggregation.

Learn to add a runtime mapping field named profit, computed as revenue minus budget, without storing it, and build a range aggregation over profit to count movies in three buckets.

Build a multi match query using a boolean must, search across title, overview, and tagline, boost the original title by two, and require vote average above 7.0.

Define and use a search template to bridge front-end queries with Elasticsearch. Test templates via underscore scripts, render template, and paginate results by taxable total price.

Define and use index aliases to route searches to indices or data streams, enabling stable front-end queries via alias names like super shop and online shop.

Discover how to highlight search terms in Elasticsearch results, apply multiple sorts (ascending/descending), and implement pagination to fetch results page by page.

Sort the results of a query by a given set of requirements within the developing search applications context, focusing on search terms and the response of a query.

Implement pagination of search results to improve query navigation within the developing search applications section, and note the guidance from lecture 32 on highlighting search terms in a query response.

Practice building an elastic search template for the movie data index, using a query parameter to search the original title, highlight results with strong tags, and sort by revenue descending.

Define and manage Elasticsearch mappings as schemas, illustrating dynamic mapping, text vs keyword, and how to update mappings via new indices and reindexing to preserve data.

Learn to build a custom analyzer in Elasticsearch by configuring character filters, tokenizers, and token filters, including HTML strip and emoji mappings, and apply it to index and search.

Define and use multi fields in Elasticsearch by storing text and keyword variants, using custom fields like city dot raw, and applying standard or English analyzers for search and aggregation.

Learn to use the reindex and update by query API to reindex or update documents, manage snapshots and shard coordination, and apply script-based field updates such as currency changes.

Learn to build and use an ingest pipeline that transforms documents with processors, converts euro to USD, adds a VIP or regular customer type, and indexes with Elasticsearch.

Define runtime fields with painless scripting to compute values on read, enabling aggregations, filtering, and sorting without indexing. Persist the mappings to make day-of-week results consistent across searches.

Practice scenario based questions for elastic certified engineer exam by using update by query to add a full address field from number, street, unit, and postcode in addresses index.

Practice a scenario with a custom analyzer and reindexing by creating a new movie index, applying lowercase and English stop words, and validate original title searches.

Explore backup and restore of a cluster or specific indices in Elasticsearch using the snapshot API, including manual and automated workflows, repositories, and retention policies.

Register a file system snapshot repository using the put snapshot API, then take a backup with a user-defined name and index pattern that includes the global state, and verify results.

Configure a base Elasticsearch cluster and a second cluster, register the remote cluster, and run a cross-cluster search across multiple indices using the comma-separated cluster syntax.

Elasticsearch demonstrates restoring and mounting searchable snapshots using the restore and snapshot APIs, enabling you to clone, restore, and search the e-commerce index from a snapshot.

Diagnose shard issues and repair a cluster's health on a single-node setup using cat shards and explain api, then fix replicas by setting them to zero and adjust disk watermarks.

Learn to implement cross cluster replication by configuring a remote cluster, setting up a leader and follower index, and enabling manual and automatic CCR across two Elasticsearch instances.