| 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 |
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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 |
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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 |
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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 |
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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 |
| 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 |
| Notes |
Print version record |
| Subject |
Information visualization.
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Electronic data processing -- Distributed processing.
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Open source softwar
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Database design & theory.
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Information visualization.
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Information architecture.
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Data capture & analysis.
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Computers -- Data Modeling & Design.
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Computers -- Data Processing.
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Electronic data processing -- Distributed processing
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Information visualization
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| Form |
Electronic book
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| Author |
Kumar, Sharath
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Chhajed, Saurabh
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Ochoa, Marcelo
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| ISBN |
9781787285866 |
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1787285863 |
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