Section 1 : Introduction

Lecture 1 Introduction to the course 5:53
Lecture 2 Introduction to Elasticsearch
Lecture 3 Overview of the Elastic Stack 17:20
Lecture 4 Walkthrough of common architectures 10:42
Lecture 5 Guidelines for the course Q&A Text

Section 2 : Getting Started

Lecture 6 Overview of installation options 2:7
Lecture 7 Running Elasticsearch & Kibana in Elastic Cloud 8:8
Lecture 8 Installing Elasticsearch on macOS and Linux 4:59
Lecture 9 Installing Elasticsearch on Windows 5:13
Lecture 10 Exploring the Elasticsearch directory 6:48
Lecture 11 Installing Kibana on macOS and Linux 3:27
Lecture 12 Installing Kibana on Windows 3:23
Lecture 13 Understanding the basic architecture 6:46
Lecture 14 Inspecting the cluster 7:33
Lecture 15 Sending queries with cURL 5:33
Lecture 16 Sharding and scalability 8:34
Lecture 17 Understanding replication 17:22
Lecture 18 Adding more nodes to the cluster (for development) 8:30
Lecture 19 Overview of node roles 9:26
Lecture 20 Wrap up 1:4

Section 3 : Managing Documents

Lecture 21 Creating & deleting indices 3:6
Lecture 22 Indexing documents 4:4
Lecture 23 Retrieving documents by ID 1:18
Lecture 24 Updating documents 3:58
Lecture 25 Scripted updates 7:42
Lecture 26 Upserts 2:29
Lecture 27 Replacing documents 1:25
Lecture 28 Deleting documents 0:59
Lecture 29 Understanding routing 5:8
Lecture 30 How Elasticsearch reads data 2:6
Lecture 31 How Elasticsearch writes data 7:55
Lecture 32 Understanding document versioning 3:12
Lecture 33 Optimistic concurrency control 6:24
Lecture 34 Update by query 8:50
Lecture 35 Delete by query 1:47
Lecture 36 Batch processing 13:52
Lecture 37 Importing data with cURL 7:2
Lecture 38 Wrap up 0:50

Section 4 : Mapping

Lecture 39 A word on document types Text
Lecture 40 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 41 Dynamic mapping 3:50
Lecture 42 Meta fields 2:48
Lecture 43 Field data types 13:46
Lecture 44 Adding mappings to existing indices 1:55
Lecture 45 Updated query Text
Lecture 46 Changing existing mappings 3:49
Lecture 47 Mapping parameters 7:58
Lecture 48 Adding multi-fields mappings 2:38
Lecture 49 Defining custom date formats
Lecture 50 Picking up new fields without dynamic mapping 7:31
Lecture 51 Wrap up 0:37

Section 5 : Analysis & Analyzers

Lecture 52 Introduction to the analysis process 1:42
Lecture 53 A closer look at analyzers 4:42
Lecture 54 Using the Analyze API 3:28
Lecture 55 Understanding the inverted index 3:20
Lecture 56 Overview of character filters 2:35
Lecture 57 Overview of tokenizers 8:35
Lecture 58 Overview of token filters 6:25
Lecture 59 Overview of built-in analyzers
Lecture 60 Configuring built-in analyzers and token filters 4:41
Lecture 61 Creating custom analyzers 3:11
Lecture 62 Using analyzers in mappings 3:18
Lecture 63 Adding analyzers to existing indices 3:27
Lecture 64 A word on stop words 1:1
Lecture 65 Wrap up 1:1

Section 6 : Introduction to Searching

Lecture 66 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 67 Search methods 1:55
Lecture 68 Searching with the request URI 3:48
Lecture 69 Introducing the Query DSL 2:25
Lecture 70 How searching works 3:33
Lecture 71 Understanding query results 1:55
Lecture 72 Understanding relevance scores 10:3
Lecture 73 Debugging unexpected search results 1:41
Lecture 74 Query contexts 2:29
Lecture 75 Full text queries vs term level queries 5:56

Section 7 : Term Level Queries

Lecture 76 Introduction to term level queries 1:11
Lecture 77 Searching for a term 2:26
Lecture 78 Searching for multiple terms 1:46
Lecture 79 Retrieving documents based on IDs 1:5
Lecture 80 Matching documents with range values 3:45
Lecture 81 Working with relative dates (date math) 7:35
Lecture 82 Matching documents with non-null values 1:58
Lecture 83 Matching based on prefixes 1:18
Lecture 84 Searching with wildcards 2:32
Lecture 85 Searching with regular expressions 3:1

Section 8 : Full Text Queries

Lecture 86 Introduction to full text queries 2:22
Lecture 87 Flexible matching with the match query 4:44
Lecture 88 Matching phrases 1:37
Lecture 89 Searching multiple fields 2:36

Section 9 : Adding Boolean Logic to Queries

Lecture 90 Introduction to compound queries 0:49
Lecture 91 Querying with boolean logic 10:36
Lecture 92 Debugging bool queries with named queries 3:15
Lecture 93 How the “match” query works 6:21

Section 10 : Joining Queries

Lecture 94 Introduction to this section 2:19
Lecture 95 Querying nested objects 5:49
Lecture 96 Nested inner hits 3:57
Lecture 97 Mapping document relationships 2:40
Lecture 98 Adding documents 6:33
Lecture 99 Querying by parent ID 2:50
Lecture 100 Querying child documents by parent 5:12
Lecture 101 Querying parent by child documents 5:54
Lecture 102 Multi-level relations 9:40
Lecture 103 Parentchild inner hits 1:59
Lecture 104 Terms lookup mechanism 6:9
Lecture 105 Join limitations 1:10
Lecture 106 Join field performance considerations 4:0

Section 11 : Controlling Query Results

Lecture 107 Specifying the result format 2:58
Lecture 108 Source filtering 4:24
Lecture 109 Specifying the result size 1:33
Lecture 110 Specifying an offset 2:8
Lecture 111 Pagination 1:51
Lecture 112 Sorting results 5:14
Lecture 113 Sorting by multi-value fields 2:26
Lecture 114 Filters 3:51

Section 12 : Aggregations

Lecture 115 Introduction to aggregations 2:21
Lecture 116 Metric aggregations 9:6
Lecture 117 Introduction to bucket aggregations
Lecture 118 Document counts are approximate 5:25
Lecture 119 Nested aggregations
Lecture 120 Filtering out documents 2:30
Lecture 121 Defining bucket rules with filters 3:14
Lecture 122 Range aggregations 7:33
Lecture 123 Histograms 7:20
Lecture 124 Global aggregation 2:57
Lecture 125 Missing field values 2:25
Lecture 126 Aggregating nested objects 2:15

Section 13 : Improving Search Results

Lecture 127 Introduction to this section 0:28
Lecture 128 Proximity searches 7:16
Lecture 129 Affecting relevance scoring with proximity 5:33
Lecture 130 Fuzzy match query (handling typos) 8:50
Lecture 131 Fuzzy query 2:31
Lecture 132 Adding synonyms 12:9
Lecture 133 Adding synonyms from file 5:38
Lecture 134 Highlighting matches in fields 6:3
Lecture 135 Stemming 5:24

Section 14 : Building a Web Application Search Engine

Lecture 136 A quick note Text
Lecture 137 Introducing Application & Client Libraries 6:40
Lecture 138 Adding a simple query 6:31
Lecture 139 Paginating search results 8:35
Lecture 140 Adding fuzziness 4:49
Lecture 141 Aggregations & Filters 17:37
Lecture 142 Adding product details page 3:41