Typically, data is available for queries within a second after being indexed (saved). Not all big data storage systems are real-time capable. Elasticsearch allows you to index thousands to hundreds of thousands of documents per second and makes them available for searching almost immediately.
Near real-time capable
by Sharath Kumar M N, Pranav Shukla
Learning Elastic Stack 7.0 - Second Edition
- Title Page
- Copyright and Credits
- About Packt
- Contributors
- Preface
- Section 1: Introduction to Elastic Stack and Elasticsearch
- Introducing Elastic Stack
- Getting Started with Elasticsearch
- Section 2: Analytics and Visualizing Data
- Searching - What is Relevant
- Analytics with Elasticsearch
- The basics of aggregations
- Preparing data for analysis
- Metric aggregations
- Bucket aggregations
- Pipeline aggregations
- Summary
- Analyzing Log Data
- Building Data Pipelines with Logstash
- Visualizing Data with Kibana
- Section 3: Elastic Stack Extensions
- Elastic X-Pack
- Section 4: Production and Server Infrastructure
- Running Elastic Stack in Production
- Hosting Elastic Stack on a managed cloud
- Hosting Elastic Stack on your own
- Backing up and restoring
- Setting up index aliases
- Setting up index templates
- Modeling time series data
- Summary
- Building a Sensor Data Analytics Application
- Introduction to the application
- Modeling data in Elasticsearch
- Setting up the metadata database
- Building the Logstash data pipeline
- Sending data to Logstash over HTTP
- Visualizing the data in Kibana
- Summary
- Monitoring Server Infrastructure
- Other Books You May Enjoy
Near real-time capable
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.