Executing Complex Queries with Elasticsearch
|
Elasticsearch is a leader in enterprise search which is the heart of most application in the digital world. This course will teach you how to build complex queries in Elasticsearch.
There are times when a basic query will not quite work with document orientated databases. In this course, Executing Complex Queries with Elasticsearch, you’ll learn to build complex queries for Elasticsearch. First, you’ll explore the basics of scoring search results. Next, you’ll discover what it takes to build join queries in Elasticsearch. Finally, you’ll learn how to develop compound queries while scoring search results. When you’re finished with this course, you’ll have the skills and knowledge of building complex queries in Elasticsearch needed to skyrocket your skills with Elasticsearch.
Author Name: Thomas Henson
Author Description:
Thomas is a Senior Software Engineer and Certified ScrumMaster. During his career he has been involved in many projects from building web applications to setting up Hadoop clusters. Thomas’s specialization is with Hortonworks Data Platform and Agile Software Development. Thomas is a proud alumnus of the University of North Alabama where he received his BBA – Computer Information System and his MBA – Information Systems. He currently resides in north Alabama with his wife and daughter, where … more
Table of Contents
- Course Overview
1min - Introduction to Complex Elasticsearch Queries
13mins - Applying Filters to Elasticsearch Queries
13mins - Utilizing Join Queries in Elasticsearch
29mins - Building Compound Queries with Elasticsearch
18mins - Moving Beyond Complex Queries
9mins
User Reviews
Be the first to review “Executing Complex Queries with Elasticsearch”
Related Products
Use Azure Synapse serverless SQL pool to query files in a data lake
With Azure Synapse serverless SQL pool, you can leverage your SQL skills to explore and analyze data in files, without the need to load the data into a relational database.
Designing Data Systems
Master the principles of designing data systems that handle large-scale data efficiently.
Use Apache Spark in Azure Databricks
Azure Databricks is built on Apache Spark and enables data engineers and analysts to run Spark jobs to transform, analyze and visualize data at scale.
Data Engineering with Microsoft Azure
Explore data engineering concepts on Microsoft Azure’s cloud platform.
Load data into a relational data warehouse
A core responsibility for a data engineer is to implement a data ingestion solution that loads new data into a relational data warehouse.
Use Delta Lake in Azure Synapse Analytics
Delta Lake is an open source relational storage area for Spark that you can use to implement a data lakehouse architecture in Azure Synapse Analytics.
There are no reviews yet.