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Learning Elastic Stack 6.0 : a beginner's guide to distributed search, analytics, and visualization using Elasticsearch, Logstash and Kibana.

Author: Pranav Shukla; Sharath Kumar; Saurabh Chhajed; Marcelo Ochoa
Publisher: Birmingham : Packt Publishing, 2017.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications. It provide in-depth coverage of the different components of the Elastic Stack, and how to use them all together.
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Shukla, Pranav.
Learning Elastic Stack 6.0 : A beginner's guide to distributed search, analytics, and visualization using Elasticsearch, Logstash and Kibana.
Birmingham : Packt Publishing, ©2017
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Pranav Shukla; Sharath Kumar; Saurabh Chhajed; Marcelo Ochoa
ISBN: 9781787285866 1787285863
OCLC Number: 1020026947
Description: 1 online resource (427 pages)
Contents: Cover --
Copyright --
Credits --
Disclaimer --
About the Authors --
About the Reviewer --
www.PacktPub.com --
Customer Feedback --
Table of Contents --
Preface --
Chapter 1: Introducing Elastic Stack --
What is Elasticsearch, and why use it? --
Schemaless and document-oriented --
Searching --
Analytics --
Rich client library support and the REST API --
Easy to operate and easy to scale --
Near real time --
Lightning fast --
Fault tolerant --
Exploring the components of Elastic Stack --
Elasticsearch --
Logstash --
Beats --
Kibana --
X-Pack --
Security --
Monitoring --
Reporting --
Alerting --
Graph --
Elastic Cloud --
Use cases of Elastic Stack --
Log and security analytics --
Product search --
Metrics analytics --
Web search and website search --
Downloading and installing --
Installing Elasticsearch --
Installing Kibana --
Summary --
Chapter 2: Getting Started with Elasticsearch --
Using the Kibana Console UI --
Core concepts --
Index --
Type --
Document --
Node --
Cluster --
Shards and replicas --
Mappings and data types --
Data types --
Core datatypes --
Complex datatypes --
Other datatypes --
Mappings --
Creating an index with the name catalog --
Defining the mappings for the type of product --
Inverted index --
CRUD operations --
Index API --
Indexing a document by providing an ID --
Indexing a document without providing an ID --
Get API --
Update API --
Delete API --
Creating indexes and taking control of mapping --
Creating an index --
Creating type mapping in an existing index --
Updating a mapping --
REST API overview --
Common API conventions --
Formatting the JSON response --
Dealing with multiple indices --
Searching all documents in one index --
Searching all documents in multiple indexes --
Searching all documents of a particular type in all indices --
Summary --
Chapter 3: Searching-What is Relevant --
Basics of text analysis. Understanding Elasticsearch analyzers --
Character filters --
Tokenizer --
Standard Tokenizer --
Token filters --
Using built-in analyzers --
Standard Analyzer --
Implementing autocomplete with a custom analyzer --
Searching from structured data --
Range query --
Range query on numeric types --
Range query with score boosting --
Range query on dates --
Exists query --
Term query --
Searching from full text --
Match query --
Operator --
minimum_should_match --
Fuzziness --
Match phrase query --
Multi match query --
Querying multiple fields with defaults --
Boosting one or more fields --
With types of multi match queries --
Writing compound queries --
Constant score query --
Bool query --
Combining OR conditions --
Combining conditions AND and OR conditions --
Adding NOT conditions --
Summary --
Chapter 4: Analytics with Elasticsearch --
The basics of aggregations --
Bucket aggregations --
Metric aggregations --
Matrix aggregations --
Pipeline aggregations --
Preparing data for analysis --
Understanding the structure of data --
Loading the data using Logstash --
Metric aggregations --
Sum, average, min, and max aggregations --
Sum aggregation --
Average aggregation --
Min aggregation --
Max aggregation --
Stats and extended stats aggregations --
Stats aggregation --
Extended stats Aggregation --
Cardinality aggregation --
Bucket aggregations --
Bucketing on string data --
Terms aggregation --
Bucketing on numeric data --
Histogram aggregation --
Range aggregation --
Aggregations on filtered data --
Nesting aggregations --
Bucketing on custom conditions --
Filter aggregation --
Filters aggregation --
Bucketing on date/time data --
Date Histogram aggregation --
Creating buckets across time --
Using a different time zone --
Computing other metrics within sliced time intervals --
Focusing on a specific day and changing intervals. Bucketing on geo-spatial data --
Geo distance aggregation --
GeoHash grid aggregation --
Pipeline aggregations --
Calculating the cumulative sum of usage over time --
Summary --
Chapter 5: Analyzing Log Data --
Log analysis challenges --
Logstash --
Installation and configuration --
Prerequisites --
Downloading and installing Logstash --
Installing on Windows --
Installing on Linux --
Running Logstash --
Logstash architecture --
Overview of Logstash plugins --
Installing or updating plugins --
Input plugins --
Output plugins --
Filter plugins --
Codec plugins --
Exploring plugins --
Exploring Input plugins --
File --
Beats --
JDBC --
IMAP --
Output plugins --
Elasticsearch --
CSV --
Kafka --
PagerDuty --
Codec plugins --
JSON --
Rubydebug --
Multiline --
Filter plugins --
Ingest node --
Defining a pipeline --
Ingest APIs --
Put pipeline API --
Get Pipeline API --
Delete pipeline API --
Simulate pipeline API --
Summary --
Chapter 6: Building Data Pipelines with Logstash --
Parsing and enriching logs using Logstash --
Filter plugins --
CSV filter --
Mutate filter --
Grok filter --
Date filter --
Geoip filter --
Useragent filter --
Introducing Beats --
Beats by Elastic.co --
Filebeat --
Metricbeat --
Packetbeat --
Heartbeat --
Winlogbeat --
Auditbeat --
Community Beats --
Logstash versus Beats --
Filebeat --
Downloading and installing Filebeat --
Installing on Windows --
Installing on Linux --
Architecture --
Configuring Filebeat --
Filebeat prospectors --
Filebeat global options --
Filebeat general options --
Output configuration --
Filebeat modules --
Summary --
Chapter 7: Visualizing data with Kibana --
Downloading and installing Kibana --
Installing on Windows --
Installing on Linux --
Configuring Kibana --
Data preparation --
Kibana UI --
User interaction --
Configuring the index pattern --
Discover --
Elasticsearch query string. Elasticsearch DSL query --
Visualize --
Kibana aggregations --
Bucket aggregations --
Metric --
Creating a visualization --
Visualization types --
Line, area, and bar charts --
Data table --
MarkDown widget --
Metric --
Goal --
Gauge --
Pie charts --
Co-ordinate maps --
Region maps --
Tag cloud --
Visualizations in action --
Response codes over time --
Top 10 URLs requested --
Bandwidth usage of top five countries over time --
Web traffic originating from different countries --
Most used user agent --
Dashboards --
Creating a dashboard --
Saving the dashboard --
Cloning the dashboard --
Sharing the dashboard --
Timelion --
Timelion UI --
Timelion expressions --
Using plugins --
Installing plugins --
Removing plugins --
Summary --
Chapter 8: Elastic X-Pack --
Installing X-Pack --
Installing X-Pack on Elasticsearch --
Installing X-Pack on Kibana --
Uninstalling X-Pack --
Configuring X-Pack --
Security --
User authentication --
User authorization --
Security in action --
New user creation --
Deleting a user --
Changing the password --
New role creation --
How to Delete/Edit a role --
Document-level security or field-level security --
X-Pack security APIs --
User management APIs --
Role management APIs --
Monitoring Elasticsearch --
Monitoring UI --
Elasticsearch metrics --
Overview tab --
Nodes tab --
The Indices tab --
Alerting --
Anatomy of a watch --
Alerting in action --
Create a new alert --
Threshold Alert --
Advanced Watch --
How to Delete/Deactivate/Edit a Watch --
Summary --
Chapter 9: Running Elastic Stack in Production --
Hosting Elastic Stack on a managed cloud --
Getting up and running on Elastic Cloud --
Using Kibana --
Overriding configuration --
Recovering from a snapshot --
Hosting Elastic Stack on your own --
Selecting hardware --
Selecting an operating system --
Configuring Elasticsearch nodes --
JVM heap size --
Disable swapping. File descriptors --
Thread pools and garbage collector --
Managing and monitoring Elasticsearch --
Running in Docker containers --
Special considerations while deploying to a cloud --
Choosing instance type --
Changing default ports --
do not expose ports! --
Proxy requests --
Binding HTTP to local addresses --
Installing EC2 discovery plugin --
Installing S3 repository plugin --
Setting up periodic snapshots --
Backing up and restoring --
Setting up a repository for snapshots --
Shared filesystem --
Cloud or distributed filesystems --
Taking snapshots --
Restoring a specific snapshot --
Setting up index aliases --
Understanding index aliases --
How index aliases can help --
Setting up index templates --
Defining an index template --
Creating indexes on the fly --
Modeling time series data --
Scaling the index with unpredictable volume over time --
Unit of parallelism in Elasticsearch --
The effect of the number of shards on the relevance score --
The effect of the number of shards on the accuracy of aggregations --
Changing the mapping over time --
New fields get added --
Existing fields get removed --
Automatically deleting older documents --
How index-per-timeframe solves these issues --
Scaling with index-per-timeframe --
Changing the mapping over time --
Automatically deleting older documents --
Summary --
Chapter 10: Building a Sensor Data Analytics Application --
Introduction to the application --
Understanding the sensor-generated data --
Understanding the sensor metadata --
Understanding the final stored data --
Modeling data in Elasticsearch --
Defining an index template --
Understanding the mapping --
Setting up the metadata database --
Building the Logstash data pipeline --
Accept JSON requests over the web --
Enrich the JSON with the metadata we have in the MySQL database --
The jdbc_streaming plugin --
The mutate plugin.

Abstract:

This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications. It provide in-depth  Read more...

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