Last updated 11/2017MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 461.49 MB | Duration: 4h 45m

Clamp the aspects of search solutions and gain knowledge on the node and cluster management facets of Elasticsearch

What you'll learn

Manage mapping, indices, and documents

Execute a search with aggregation

Create a REST and an ingest plugin

Index data via Apache Spark

Control cluster health and state via an API

Use the task management and Hot thread API

Manage repositories

Requirements

Basic understanding of JSON is needed.

Prior knowledge on Elasticsearch is assumed.

Description

Elasticsearch is a popular search ee based on Lucene. It provides a distributed, multitenant-capable, full-text search ee with an HTTP web interface and schema-free JSON documents. Elasticsearch is a distributed, RESTful search and analytics ee capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected. So, if you're interested to create flexible and scalable search solutions using Elasticsearch and get knowledge of the node and cluster aspects, then go for this Learning Path.

Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

The highlights of this Learning Path are

Learn to manage mapping, indices, and documents

Use the task management and Hot thread API

Let’s take a quick look at your learning journey. This Learning Path dives into the third-party integration aspect of Elasticsearch. It gives you a detailed coverage of how Elasticsearch can be integrated with popular languages such as Python, Java, and Scala, as well as shows you how Elasticsearch is integrated with third-party tools for efficient big data solutions. Further, you will learn practical recipes on the major operations such as searching, working with text, numeric and geo queries, perfog aggregations and scripting. Moving on you will dive into node and cluster management aspects of Elasticsearch. You will be acquainted with recipes and hands-on solutions to backing up and restoring your nodes and clusters in Elasticsearch, as well as working with user interfaces.

By the end of this Learning Path, you will be able to integrate Elasticsearch with Java, Python, Scala and create flexible and scalable search solutions.

Meet Your Expert

We have combined the best works of the following esteemed author to ensure that your learning journey is smooth

Alberto Paro is an eeer, project manager, and software developer. He currently works as freelance trainer/consultant on big data technologies and NoSQL solutions. He loves to study emeg solutions and applications mainly related to big data processing, NoSQL, natural language processing, and neural networks. He began programming in BASIC on a Sinclair Spectrum when he was eight years old, and to date, has collected a lot of experience using different operating systems, applications, and programming languages.

Overview

Section 1: Elasticsearch 5.x Solutions - Extending Elasticsearch

Lecture 1 The Course Overview

Lecture 2 Creating Clients

Lecture 3 Managing Indices with the Native Client

Lecture 4 Managing Mappings, Documents, and Bulk Actions

Lecture 5 Building a Query

Lecture 6 Executing Search

Lecture 7 Creating a Client in Scala

Lecture 8 Managing Indices

Lecture 9 Managing Mappings

Lecture 10 Managing Documents

Lecture 11 Executing a Standard Search

Lecture 12 Executing a Search with Aggregations

Lecture 13 Creating a Client

Lecture 14 Managing Indices

Lecture 15 Managing Mappings

Lecture 16 Managing Documents

Lecture 17 Executing a Standard Search

Lecture 18 Executing a Search with Aggregations

Lecture 19 Creating a Plugin

Lecture 20 Creating an Analyzer Plugin

Lecture 21 Creating a REST Plugin

Lecture 22 Creating a Cluster Action

Lecture 23 Creating an Ingest Plugin

Section 2: Elasticsearch 5.x Solutions - Mastering Elasticsearch Operations

Lecture 24 The Course Overview

Lecture 25 Searching, Sorting, and Highlighting Results

Lecture 26 Scrolling and Returning Inner Hits

Lecture 27 Suggesting Correct Query and Counting Matched Results

Lecture 28 Query and Query Profiling

Lecture 29 Deleting and Updating by Query

Lecture 30 Matching All Documents and Using a Boolean Query

Lecture 31 Using a Term and Prefix Query

Lecture 32 Using wildcard, regexp, and Span Query

Lecture 33 Using a Match and Query String Query

Lecture 34 Using Range, Common Term, and IDs Query

Lecture 35 Using the Function Score, Exist, and Template Query

Lecture 36 Using the has_child Query

Lecture 37 Using the has_parent Query

Lecture 38 Using the geo_bounding_box Query

Lecture 39 Using the geo_polygon Query

Lecture 40 Using the geo_distance Query

Lecture 41 Executing Stats and Terms Aggregation

Lecture 42 Executing Range and Histogram Aggregations

Lecture 43 Executing Filter Aggregations

Lecture 44 Executing Global, Geo Distance, and Children Aggregation

Lecture 45 Executing Nested, Top Hit, and Matrix Stats Aggregation

Lecture 46 Executing the geo_bound and geo_centroid Aggregation

Lecture 47 Painless Scripting

Lecture 48 Installing Additional Scripts Plugins

Section 3: Elasticsearch 5.x Solutions - Node and Cluster Management

Lecture 49 The Course Overview

Lecture 50 Controlling Cluster Health and State Via an API

Lecture 51 Getting Nodes Information and Statistics Via API

Lecture 52 Using the Task Management and the Hot thread API

Lecture 53 Managing the Shard Allocation

Lecture 54 Monitoring Snts and Clearing the Cache

Lecture 55 Managing Repositories

Lecture 56 Executing a Snapshot

Lecture 57 Restoring a Snapshot

Lecture 58 Reindexing from a Remote Cluster

Lecture 59 Installing and Using Cerebro

Lecture 60 Installing Kibana and X-Pack

Lecture 61 Managing Kibana Dashboards

Lecture 62 Monitoring with Kibana

Lecture 63 Using Kibana dev-console

Lecture 64 Visualizing Data with Kibana

Lecture 65 Pipeline Definition

Lecture 66 PUT, GET, and DELETE an Ingest Pipeline

Lecture 67 Simulating an Ingest Pipeline

Lecture 68 Built-in and Grok Processors

Lecture 69 Using the Ingest Attachment and GeoIP Plugin

If you are a developer who wants to get the most out of Elasticsearch for advanced search and analytics, then this Learning Path is for you.

HomePage: