Elasticsearch 完整指南
上次更新时间：2024-12-03
课程售价: 2.9 元
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课程内容
01 - Introduction
02 - Getting Started
- 001 Overview of installation options
- 002 Running Elasticsearch & Kibana in Elastic Cloud
- 003 Setting up Elasticsearch & Kibana on macOS & Linux
- 004 Setting up Elasticsearch & Kibana on Windows
- 005 Understanding the basic architecture
- 006 Inspecting the cluster
- 007 Sending queries with cURL
- 008 Sharding and scalability
- 010 Understanding replication
- 012 Adding more nodes to the cluster
- 013 Overview of node roles
- 014 Wrap up
03 - Managing Documents
- 001 Creating & deleting indices
- 002 Indexing documents
- 003 Retrieving documents by ID
- 004 Updating documents
- 005 Scripted updates
- 006 Upserts
- 007 Replacing documents
- 008 Deleting documents
- 009 Understanding routing
- 010 How Elasticsearch reads data
- 011 How Elasticsearch writes data
- 012 Understanding document versioning
- 013 Optimistic concurrency control
- 014 Update by query
- 015 Delete by query
- 016 Batch processing
- 017 Importing data with cURL
- 018 Wrap up
04 - Mapping & Analysis
- 001 Introduction to this section
- 002 Introduction to analysis
- 003 Using the Analyze API
- 004 Understanding inverted indices
- 005 Introduction to mapping
- 006 Overview of data types
- 007 How the keyword data type works
- 008 Understanding type coercion
- 009 Understanding arrays
- 010 Adding explicit mappings
- 011 Retrieving mappings
- 012 Using dot notation in field names
- 013 Adding mappings to existing indices
- 014 How dates work in Elasticsearch
- 015 How missing fields are handled
- 016 Overview of mapping parameters
- 017 Updating existing mappings
- 018 Reindexing documents with the Reindex API
- 019 Defining field aliases
- 020 Multi-field mappings
- 021 Index templates
- 022 Introduction to the Elastic Common Schema (ECS)
- 023 Introduction to dynamic mapping
- 024 Combining explicit and dynamic mapping
- 025 Configuring dynamic mapping
- 026 Dynamic templates
- 027 Mapping recommendations
- 028 Stemming & stop words
- 029 Analyzers and search queries
- 030 Built-in analyzers
- 031 Creating custom analyzers
- 032 Adding analyzers to existing indices
- 033 Updating analyzers
- 034 Wrap up
05 - Searching for Data
- 001 Introduction to searching
- 002 Introduction to term level queries
- 003 Searching for terms
- 004 Retrieving documents by IDs
- 005 Range searches
- 006 Prefixes, wildcards & regular expressions
- 007 Querying by field existence
- 009 Introduction to full text queries
- 010 The match query
- 011 Introduction to relevance scoring
- 012 Searching multiple fields
- 013 Phrase searches
- 015 Leaf and compound queries
- 016 Querying with boolean logic
- 017 Query execution contexts
- 018 Boosting query
- 019 Disjunction max (dis_max)
- 020 Querying nested objects
- 021 Nested inner hits
- 022 Nested fields limitations
06 - Joining Queries
- 001 Introduction to this section
- 003 Mapping document relationships
- 004 Adding documents
- 005 Querying by parent ID
- 006 Querying child documents by parent
- 007 Querying parent by child documents
- 008 Multi-level relations
- 009 Parentchild inner hits
- 010 Terms lookup mechanism
- 011 Join limitations
- 012 Join field performance considerations
07 - Controlling Query Results
08 - Aggregations
- 001 Introduction to aggregations
- 002 Metric aggregations
- 003 Introduction to bucket aggregations
- 004 Document counts are approximate
- 005 Nested aggregations
- 006 Filtering out documents
- 007 Defining bucket rules with filters
- 008 Range aggregations
- 009 Histograms
- 010 Global aggregation
- 011 Missing field values
- 012 Aggregating nested objects
课程内容
9个章节 , 128个讲座
01 - Introduction
02 - Getting Started
- 001 Overview of installation options
- 002 Running Elasticsearch & Kibana in Elastic Cloud
- 003 Setting up Elasticsearch & Kibana on macOS & Linux
- 004 Setting up Elasticsearch & Kibana on Windows
- 005 Understanding the basic architecture
- 006 Inspecting the cluster
- 007 Sending queries with cURL
- 008 Sharding and scalability
- 010 Understanding replication
- 012 Adding more nodes to the cluster
- 013 Overview of node roles
- 014 Wrap up
03 - Managing Documents
- 001 Creating & deleting indices
- 002 Indexing documents
- 003 Retrieving documents by ID
- 004 Updating documents
- 005 Scripted updates
- 006 Upserts
- 007 Replacing documents
- 008 Deleting documents
- 009 Understanding routing
- 010 How Elasticsearch reads data
- 011 How Elasticsearch writes data
- 012 Understanding document versioning
- 013 Optimistic concurrency control
- 014 Update by query
- 015 Delete by query
- 016 Batch processing
- 017 Importing data with cURL
- 018 Wrap up
04 - Mapping & Analysis
- 001 Introduction to this section
- 002 Introduction to analysis
- 003 Using the Analyze API
- 004 Understanding inverted indices
- 005 Introduction to mapping
- 006 Overview of data types
- 007 How the keyword data type works
- 008 Understanding type coercion
- 009 Understanding arrays
- 010 Adding explicit mappings
- 011 Retrieving mappings
- 012 Using dot notation in field names
- 013 Adding mappings to existing indices
- 014 How dates work in Elasticsearch
- 015 How missing fields are handled
- 016 Overview of mapping parameters
- 017 Updating existing mappings
- 018 Reindexing documents with the Reindex API
- 019 Defining field aliases
- 020 Multi-field mappings
- 021 Index templates
- 022 Introduction to the Elastic Common Schema (ECS)
- 023 Introduction to dynamic mapping
- 024 Combining explicit and dynamic mapping
- 025 Configuring dynamic mapping
- 026 Dynamic templates
- 027 Mapping recommendations
- 028 Stemming & stop words
- 029 Analyzers and search queries
- 030 Built-in analyzers
- 031 Creating custom analyzers
- 032 Adding analyzers to existing indices
- 033 Updating analyzers
- 034 Wrap up
05 - Searching for Data
- 001 Introduction to searching
- 002 Introduction to term level queries
- 003 Searching for terms
- 004 Retrieving documents by IDs
- 005 Range searches
- 006 Prefixes, wildcards & regular expressions
- 007 Querying by field existence
- 009 Introduction to full text queries
- 010 The match query
- 011 Introduction to relevance scoring
- 012 Searching multiple fields
- 013 Phrase searches
- 015 Leaf and compound queries
- 016 Querying with boolean logic
- 017 Query execution contexts
- 018 Boosting query
- 019 Disjunction max (dis_max)
- 020 Querying nested objects
- 021 Nested inner hits
- 022 Nested fields limitations
06 - Joining Queries
- 001 Introduction to this section
- 003 Mapping document relationships
- 004 Adding documents
- 005 Querying by parent ID
- 006 Querying child documents by parent
- 007 Querying parent by child documents
- 008 Multi-level relations
- 009 Parentchild inner hits
- 010 Terms lookup mechanism
- 011 Join limitations
- 012 Join field performance considerations
07 - Controlling Query Results
08 - Aggregations
- 001 Introduction to aggregations
- 002 Metric aggregations
- 003 Introduction to bucket aggregations
- 004 Document counts are approximate
- 005 Nested aggregations
- 006 Filtering out documents
- 007 Defining bucket rules with filters
- 008 Range aggregations
- 009 Histograms
- 010 Global aggregation
- 011 Missing field values
- 012 Aggregating nested objects