Elasticsearch Server Second Edition -- Table of Contents -- Elasticsearch Server Second Edition -- Credits -- About the Author -- Acknowledgments -- About the Author -- Acknowledgments -- About the Reviewers -- www.PacktPub.com -- Support files, eBooks, discount offers, and more -- Why subscribe? -- Free access for Packt account holders -- Preface -- What this book covers -- What you need for this book -- Who this book is for -- Conventions -- Reader feedback -- Customer support -- Downloading the example code -- Errata -- Piracy -- Questions -- 1. Getting Started with the Elasticsearch Cluster -- Full-text searching -- The Lucene glossary and architecture -- Input data analysis -- Indexing and querying -- Scoring and query relevance -- The basics of Elasticsearch -- Key concepts of data architecture -- Index -- Document -- Document type -- Mapping -- Key concepts of Elasticsearch -- Node and cluster -- Shard -- Replica -- Gateway -- Indexing and searching -- Installing and configuring your cluster -- Installing Java -- Installing Elasticsearch -- Installing Elasticsearch from binary packages on Linux -- Installing Elasticsearch using the RPM package -- Installing Elasticsearch using the DEB package -- The directory layout -- Configuring Elasticsearch -- Running Elasticsearch -- Shutting down Elasticsearch -- Running Elasticsearch as a system service -- Elasticsearch as a system service on Linux -- Elasticsearch as a system service on Windows -- Manipulating data with the REST API -- Understanding the Elasticsearch RESTful API -- Storing data in Elasticsearch -- Creating a new document -- Automatic identifier creation -- Retrieving documents -- Updating documents -- Deleting documents -- Versioning -- An example of versioning -- Using the version provided by an external system -- Searching with the URI request query -- Sample data.

The URI request -- The Elasticsearch query response -- Query analysis -- URI query string parameters -- The query -- The default search field -- Analyzer -- The default operator -- Query explanation -- The fields returned -- Sorting the results -- The search timeout -- The results window -- The search type -- Lowercasing the expanded terms -- Analyzing the wildcard and prefixes -- The Lucene query syntax -- Summary -- 2. Indexing Your Data -- Elasticsearch indexing -- Shards and replicas -- Creating indices -- Altering automatic index creation -- Settings for a newly created index -- Mappings configuration -- Type determining mechanism -- Disabling field type guessing -- Index structure mapping -- Type definition -- Fields -- Core types -- Common attributes -- String -- Number -- Boolean -- Binary -- Date -- Multifields -- The IP address type -- The token_count type -- Using analyzers -- Out-of-the-box analyzers -- Defining your own analyzers -- Analyzer fields -- Default analyzers -- Different similarity models -- Setting per-field similarity -- Available similarity models -- Configuring DFR similarity -- Configuring IB similarity -- The postings format -- Configuring the postings format -- Doc values -- Configuring the doc values -- Doc values formats -- Batch indexing to speed up your indexing process -- Preparing data for bulk indexing -- Indexing the data -- Even quicker bulk requests -- Extending your index structure with additional internal information -- Identifier fields -- The _type field -- The _all field -- The _source field -- Exclusion and inclusion -- The _index field -- The _size field -- The _timestamp field -- The _ttl field -- Introduction to segment merging -- Segment merging -- The need for segment merging -- The merge policy -- The merge scheduler -- The merge factor -- Throttling -- Introduction to routing -- Default indexing.

Default searching -- Routing -- The routing parameters -- Routing fields -- Summary -- 3. Searching Your Data -- Querying Elasticsearch -- The example data -- A simple query -- Paging and result size -- Returning the version value -- Limiting the score -- Choosing the fields that we want to return -- The partial fields -- Using the script fields -- Passing parameters to the script fields -- Understanding the querying process -- Query logic -- Search types -- Search execution preferences -- The Search shards API -- Basic queries -- The term query -- The terms query -- The match_all query -- The common terms query -- The match query -- The Boolean match query -- The match_phrase query -- The match_phrase_prefix query -- The multi_match query -- The query_string query -- Running the query_string query against multiple fields -- The simple_query_string query -- The identifiers query -- The prefix query -- The fuzzy_like_this query -- The fuzzy_like_this_field query -- The fuzzy query -- The wildcard query -- The more_like_this query -- The more_like_this_field query -- The range query -- The dismax query -- The regular expression query -- Compound queries -- The bool query -- The boosting query -- The constant_score query -- The indices query -- Filtering your results -- Using filters -- Filter types -- The range filter -- The exists filter -- The missing filter -- The script filter -- The type filter -- The limit filter -- The identifiers filter -- If this is not enough -- Combining filters -- A word about the bool filter -- Named filters -- Caching filters -- Highlighting -- Getting started with highlighting -- Field configuration -- Under the hood -- Configuring HTML tags -- Controlling the highlighted fragments -- Global and local settings -- Require matching -- The postings highlighter -- Validating your queries -- Using the validate API.

Sorting data -- Default sorting -- Selecting fields used for sorting -- Specifying the behavior for missing fields -- Dynamic criteria -- Collation and national characters -- Query rewrite -- An example of the rewrite process -- Query rewrite properties -- Summary -- 4. Extending Your Index Structure -- Indexing tree-like structures -- Data structure -- Analysis -- Indexing data that is not flat -- Data -- Objects -- Arrays -- Mappings -- Final mappings -- Sending the mappings to Elasticsearch -- To be or not to be dynamic -- Using nested objects -- Scoring and nested queries -- Using the parent-child relationship -- Index structure and data indexing -- Parent mappings -- Child mappings -- The parent document -- The child documents -- Querying -- Querying data in the child documents -- The top children query -- Querying data in the parent documents -- The parent-child relationship and filtering -- Performance considerations -- Modifying your index structure with the update API -- The mappings -- Adding a new field -- Modifying fields -- Summary -- 5. Make Your Search Better -- An introduction to Apache Lucene scoring -- When a document is matched -- Default scoring formula -- Relevancy matters -- Scripting capabilities of Elasticsearch -- Objects available during script execution -- MVEL -- Using other languages -- Using our own script library -- Using native code -- The factory implementation -- Implementing the native script -- Installing scripts -- Running the script -- Searching content in different languages -- Handling languages differently -- Handling multiple languages -- Detecting the language of the documents -- Sample document -- The mappings -- Querying -- Queries with the identified language -- Queries with unknown languages -- Combining queries -- Influencing scores with query boosts -- The boost -- Adding boost to queries.

Modifying the score -- The constant_score query -- The boosting query -- The function_score query -- The structure of the function query -- Deprecated queries -- Replacing the custom_boost_factor query -- Replacing the custom_score query -- Replacing the custom_filters_score query -- When does index-time boosting make sense? -- Defining field boosting in input data -- Defining boosting in mapping -- Words with the same meaning -- The synonym filter -- Synonyms in the mappings -- Synonyms stored in the filesystem -- Defining synonym rules -- Using Apache Solr synonyms -- Explicit synonyms -- Equivalent synonyms -- Expanding synonyms -- Using WordNet synonyms -- Query- or index-time synonym expansion -- Understanding the explain information -- Understanding field analysis -- Explaining the query -- Summary -- 6. Beyond Full-text Searching -- Aggregations -- General query structure -- Available aggregations -- Metric aggregations -- Min, max, sum, and avg aggregations -- Using scripts -- The value_count aggregation -- The stats and extended_stats aggregations -- Bucketing -- The terms aggregation -- The range aggregation -- The date_range aggregation -- IPv4 range aggregation -- The missing aggregation -- Nested aggregation -- The histogram aggregation -- The date_histogram aggregation -- Time zones -- The geo_distance aggregation -- The geohash_grid aggregation -- Nesting aggregations -- Bucket ordering and nested aggregations -- Global and subsets -- Inclusions and exclusions -- Faceting -- The document structure -- Returned results -- Using queries for faceting calculations -- Using filters for faceting calculations -- Terms faceting -- Ranges based faceting -- Choosing different fields for an aggregated data calculation -- Numerical and date histogram faceting -- The date_histogram facet -- Computing numerical field statistical data.

Computing statistical data for terms.