Bo Andersen – Complete Guide to Elasticsearch

Creating an index (1:34)

Adding documents (3:49)

Retrieving documents by ID (1:16)

Replacing documents (1:29)

Updating documents (3:42)

Scripted updates (3:08)

Upserts (2:32)

Deleting documents (3:30)

Deleting indices (0:49)

Batch processing (5:56)

Importing test data – cURL (2:51)

Exploring the cluster (6:53)

Introduction to mapping (1:23)

Dynamic mapping (4:27)

Meta fields (2:50)

Field data types (13:48)

Adding mappings to existing indices (1:57)

Changing existing mappings (3:51)

Mapping parameters (8:02)

Adding multi-fields mappings (2:40)

Defining custom date formats (5:46)

Picking up new fields -out dynamic mapping (7:33)

Wrap up (0:37)

Introduction to the analysis process (1:53)

A closer look at analyzers (5:21)

Using the Analyze API (3:30)

Understanding the inverted index (4:31)

Quiz

Overview of character filters (2:36)

Overview of tokenizers (8:36)

Overview of token filters (6:26)

Overview of built-in analyzers (5:00)

Configuring built-in analyzers and token filters (4:43)

Creating custom analyzers (3:13)

Using analyzers in mappings (3:20)

Adding analyzers to existing indices (3:30)

A word on stop words (1:01)

Wrap up (1:01)

Search methods (2:17)

Searching – the request URI (3:50)

Introducing the Query DSL (2:50)

Understanding query results (1:57)

Understanding relevance scores (10:30)

Debugging unexpected search results (1:43)

Query contexts (2:40)

Full text queries vs term level queries (5:57)

Quiz

Introduction to term level queries (1:10)

Searching for a term (2:28)

Searching for multiple terms (1:48)

Retrieving documents based on IDs (1:07)

Matching documents – range values (3:46)

Working – relative dates (date math) (7:37)

Matching documents – non-null values (2:00)

Matching based on prefixes (1:19)

Searching – wildcards (2:34)

Searching – regular expressions (3:03)

Exercises (1:07)

Exercises: Solutions (6:16)

Introduction to full text queries (2:23)

Flexible matching – match query (4:45)

Matching phrases (1:38)

Searching multiple fields (2:38)

Exercises (0:40)

Exercises: Solutions (2:29)

Introduction to compound queries (1:09)

Querying – boolean logic (10:37)

Debugging bool queries – named queries (3:16)

How the “match” query works (6:27)

Introduction to this section

Querying nested objects (5:21)

Specifying the result format (3:01)

Source filtering (4:26)

Specifying the result size (1:36)

Specifying an offset (2:09)

Pagination (5:04)

Sorting results (5:16)

Sorting by multi-value fields (2:27)

Filters (3:52)

Introduction to aggregations (2:43)

Metric aggregations (9:40)

Introduction to bucket aggregations (6:25)

Document counts are approximate (6:22)

Nested aggregations (5:58)

Filtering out documents (2:31)

Defining bucket rules – filters (3:16)

Range aggregations (7:54)

Histograms (8:01)

Global aggregation (2:59)

Missing field values (2:27)

Aggregating nested objects (2:16)

Introduction to this section (0:27)

Proximity searches (7:17)

Affecting relevance scoring – proximity (5:34)

Fuzzy match query (handling typos) (9:06)

Fuzzy query (2:33)

Adding synonyms

Adding synonyms from file (5:40)

Highlighting matches in fields (6:05)

Stemming (5:26)