Урок 1.00:06:28
Introduction to the course
Урок 2.00:06:37
Introduction to Elasticsearch
Урок 3.00:17:47
Overview of the Elastic Stack
Урок 4.00:10:58
Walkthrough of common architectures
Урок 5.00:02:36
Overview of installation options
Урок 6.00:05:36
Running Elasticsearch & Kibana in Elastic Cloud
Урок 7.00:07:51
Setting up Elasticsearch & Kibana on macOS & Linux
Урок 8.00:06:59
Setting up Elasticsearch & Kibana on Windows
Урок 9.00:06:58
Understanding the basic architecture
Урок 10.00:07:41
Inspecting the cluster
Урок 11.00:08:16
Sending queries with cURL
Урок 12.00:09:28
Sharding and scalability
Урок 13.00:17:41
Understanding replication
Урок 14.00:12:22
Adding more nodes to the cluster
Урок 15.00:10:00
Overview of node roles
Урок 16.00:01:11
Wrap up
Урок 17.00:03:09
Creating & deleting indices
Урок 18.00:04:07
Indexing documents
Урок 19.00:01:21
Retrieving documents by ID
Урок 20.00:04:01
Updating documents
Урок 21.00:07:45
Scripted updates
Урок 22.00:02:31
Upserts
Урок 23.00:01:27
Replacing documents
Урок 24.00:01:02
Deleting documents
Урок 25.00:05:19
Understanding routing
Урок 26.00:02:35
How Elasticsearch reads data
Урок 27.00:08:04
How Elasticsearch writes data
Урок 28.00:03:23
Understanding document versioning
Урок 29.00:06:33
Optimistic concurrency control
Урок 30.00:08:53
Update by query
Урок 31.00:01:53
Delete by query
Урок 32.00:13:55
Batch processing
Урок 33.00:07:15
Importing data with cURL
Урок 34.00:00:53
Wrap up
Урок 35.00:00:43
Introduction to this section
Урок 36.00:05:31
Introduction to analysis
Урок 37.00:05:13
Using the Analyze API
Урок 38.00:06:41
Understanding inverted indices
Урок 39.00:02:09
Introduction to mapping
Урок 40.00:08:36
Overview of data types
Урок 41.00:04:09
How the "keyword" data type works
Урок 42.00:06:00
Understanding type coercion
Урок 43.00:05:05
Understanding arrays
Урок 44.00:05:33
Adding explicit mappings
Урок 45.00:01:36
Retrieving mappings
Урок 46.00:01:50
Using dot notation in field names
Урок 47.00:01:53
Adding mappings to existing indices
Урок 48.00:06:06
How dates work in Elasticsearch
Урок 49.00:01:45
How missing fields are handled
Урок 50.00:14:36
Overview of mapping parameters
Урок 51.00:04:22
Updating existing mappings
Урок 52.00:12:47
Reindexing documents with the Reindex API
Урок 53.00:03:32
Defining field aliases
Урок 54.00:06:35
Multi-field mappings
Урок 55.00:07:51
Index templates
Урок 56.00:05:31
Introduction to the Elastic Common Schema (ECS)
Урок 57.00:09:03
Introduction to dynamic mapping
Урок 58.00:01:35
Combining explicit and dynamic mapping
Урок 59.00:08:03
Configuring dynamic mapping
Урок 60.00:13:23
Dynamic templates
Урок 61.00:05:16
Mapping recommendations
Урок 62.00:04:09
Stemming & stop words
Урок 63.00:04:23
Analyzers and search queries
Урок 64.00:07:39
Built-in analyzers
Урок 65.00:10:01
Creating custom analyzers
Урок 66.00:06:12
Adding analyzers to existing indices
Урок 67.00:07:09
Updating analyzers
Урок 68.00:00:29
Wrap up
Урок 69.00:02:18
Search methods
Урок 70.00:03:51
Searching with the request URI
Урок 71.00:02:51
Introducing the Query DSL
Урок 72.00:03:43
How searching works
Урок 73.00:01:58
Understanding query results
Урок 74.00:10:31
Understanding relevance scores
Урок 75.00:01:44
Debugging unexpected search results
Урок 76.00:02:42
Query contexts
Урок 77.00:05:59
Full text queries vs term level queries
Урок 78.00:01:11
Introduction to term level queries
Урок 79.00:02:29
Searching for a term
Урок 80.00:01:49
Searching for multiple terms
Урок 81.00:01:08
Retrieving documents based on IDs
Урок 82.00:03:47
Matching documents with range values
Урок 83.00:07:38
Working with relative dates (date math)
Урок 84.00:02:01
Matching documents with non-null values
Урок 85.00:01:20
Matching based on prefixes
Урок 86.00:02:35
Searching with wildcards
Урок 87.00:03:04
Searching with regular expressions
Урок 88.00:02:24
Introduction to full text queries
Урок 89.00:04:46
Flexible matching with the match query
Урок 90.00:01:39
Matching phrases
Урок 91.00:02:39
Searching multiple fields
Урок 92.00:01:10
Introduction to compound queries
Урок 93.00:10:38
Querying with boolean logic
Урок 94.00:03:18
Debugging bool queries with named queries
Урок 95.00:06:24
How the “match” query works
Урок 96.00:02:44
Introduction to this section
Урок 97.00:05:52
Querying nested objects
Урок 98.00:04:00
Nested inner hits
Урок 99.00:02:43
Mapping document relationships
Урок 100.00:06:36
Adding documents
Урок 101.00:02:53
Querying by parent ID
Урок 102.00:05:15
Querying child documents by parent
Урок 103.00:05:56
Querying parent by child documents
Урок 104.00:09:43
Multi-level relations
Урок 105.00:02:02
Parent/child inner hits
Урок 106.00:06:12
Terms lookup mechanism
Урок 107.00:01:43
Join limitations
Урок 108.00:04:21
Join field performance considerations
Урок 109.00:03:02
Specifying the result format
Урок 110.00:04:27
Source filtering
Урок 111.00:01:37
Specifying the result size
Урок 112.00:02:10
Specifying an offset
Урок 113.00:05:05
Pagination
Урок 114.00:05:17
Sorting results
Урок 115.00:02:29
Sorting by multi-value fields
Урок 116.00:03:53
Filters
Урок 117.00:02:44
Introduction to aggregations
Урок 118.00:09:42
Metric aggregations
Урок 119.00:06:26
Introduction to bucket aggregations
Урок 120.00:06:23
Document counts are approximate
Урок 121.00:05:59
Nested aggregations
Урок 122.00:02:32
Filtering out documents
Урок 123.00:03:17
Defining bucket rules with filters
Урок 124.00:07:55
Range aggregations
Урок 125.00:08:02
Histograms
Урок 126.00:03:00
Global aggregation
Урок 127.00:02:28
Missing field values
Урок 128.00:02:17
Aggregating nested objects
Урок 129.00:00:28
Introduction to this section
Урок 130.00:07:18
Proximity searches
Урок 131.00:05:35
Affecting relevance scoring with proximity
Урок 132.00:09:07
Fuzzy match query (handling typos)
Урок 133.00:02:34
Fuzzy query
Урок 134.00:12:12
Adding synonyms
Урок 135.00:05:41
Adding synonyms from file
Урок 136.00:06:06
Highlighting matches in fields
Урок 137.00:05:27
Stemming