Learning Elasticsearch : Store, Search, and Analyze Your Data with Ease Using Elasticsearch 5. x.

Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Introduction to Elasticsearch -- Basic concepts of Elasticsearch -- Document -- Index -- Type -- Cluster and node -- Shard -- Interacting with Elasticsearch -- Creating a document -- Retrieving an existing document -- Updating an existing document -- Updating a partial document -- Deleting an existing document -- How does search work? -- Importance of information retrieval -- Simple search query -- Inverted index -- Stemming -- Synonyms -- Phrase search -- Apache Lucene -- Scalability and availability -- Relation between node, index, and shard -- Three shards with zero replicas -- Six shards with zero replicas -- Six shards with one replica -- Distributed search -- Failure handling -- Strengths and limitations of Elasticsearch -- Summary -- Chapter 2: Setting Up Elasticsearch and Kibana -- Installing Elasticsearch -- Installing Java -- Windows -- Starting and stopping Elasticsearch -- Mac OS X -- Starting and stopping Elasticsearch -- DEB and RPM packages -- Debian package -- RPM package -- Starting and stopping Elasticsearch -- Sample configuration files -- Verifying Elasticsearch is running -- Installing Kibana -- Mac OS X -- Starting and stopping Kibana -- Windows -- Starting and stopping Kibana -- Query format used in this book (Kibana Console) -- Using cURL or Postman -- Health of the cluster -- Summary -- Chapter 3: Modeling Your Data and Document Relations -- Mapping -- Dynamic mapping -- Create index with mapping -- Adding a new type/field -- Getting the existing mapping -- Mapping conflicts -- Data type -- Metafields -- How to handle null values -- Storing the original document -- Searching all the fields in the document -- Difference between full-text search and exact match.

Core data types -- Text -- Keyword -- Date -- Numeric -- Boolean -- Binary -- Complex data types -- Array -- Object -- Nested -- Geo data type -- Geo-point data type -- Specialized data type -- IP -- Mapping the same field with different mappings -- Handling relations between different document types -- Parent-child document relation -- How are parent-child documents stored internally? -- Nested -- Routing -- Summary -- Chapter 4: Indexing and Updating Your Data -- Indexing your data -- Indexing errors -- Node/shards errors -- Serialization/mapping errors -- Thread pool rejection error -- Managing an index -- What happens when you index a document? -- Updating your data -- Update using an entire document -- Partial updates -- Scripted updates -- Upsert -- NOOP -- What happens when you update a document? -- Merging segments -- Using Kibana to discover -- Using Elasticsearch in your application -- Java -- Transport client -- Dependencies -- Initializing the client -- Sniffing -- Node client -- REST client -- Third party clients -- Indexing using Java client -- Concurrency -- Translog -- Async versus sync -- CRUD from translog -- Primary and Replica shards -- Primary preference -- More replicas for query throughput -- Increasing/decreasing the number of replicas -- Summary -- Chapter 5: Organizing Your Data and Bulk Data Ingestion -- Bulk operations -- Bulk API -- Multi Get API -- Update by query -- Delete by query -- Reindex API -- Change mappings/settings -- Combining documents from one or more indices -- Copying only missing documents -- Copying a subset of documents into a new index -- Copying top N documents -- Copying the subset of fields into new index -- Ingest Node -- Organizing your data -- Index alias -- Index templates -- Managing time-based indices -- Shrink API -- Summary -- Chapter 6: All About Search -- Different types of queries.

Sample data -- Querying Elasticsearch -- Basic query (finding the exact value) -- Pagination -- Sorting based on existing fields -- Selecting the fields in the response -- Querying based on range -- Handling dates -- Analyzed versus non-analyzed fields -- Term versus Match query -- Match phrase query -- Prefix and match phrase prefix query -- Wildcard and Regular expression query -- Exists and missing queries -- Using more than one query -- Routing -- Debugging search query -- Relevance -- Queries versus Filters -- How to boost relevance based on a single field -- How to boost score based on queries -- How to boost relevance using decay functions -- Rescoring -- Debugging relevance score -- Searching for same value across multiple fields -- Best matching fields -- Most matching fields -- Cross-matching fields -- Caching -- Node Query cache -- Shard request cache -- Summary -- Chapter 7: More Than a Search Engine (Geofilters, Autocomplete, and More) -- Sample data -- Correcting typos and spelling mistakes -- Fuzzy query -- Making suggestions based on the user input -- Implementing -- Term suggester -- Phrase suggester -- Implementing the autocomplete feature -- Highlighting -- Handling document relations using parent-child -- The has_parent query -- The has_child query -- Inner hits for parent-child -- How parent-child works internally -- Handling document relations using nested -- Inner hits for nested documents -- Scripting -- Script Query -- Post Filter -- Reverse search using the percolate query -- Geo and Spatial Filtering -- Geo Distance -- Using Geolocation to rank the search results -- Geo Bounding Box -- Sorting -- Multi search -- Search templates -- Querying Elasticsearch from Java application -- Summary -- Chapter 8: How to Slice and Dice Your Data Using Aggregations -- Aggregation basics -- Sample data -- Query structure.

Multilevel aggregations -- Types of aggregations -- Terms aggregations (group by) -- Size and error -- Order -- Minimum document count -- Missing values -- Aggregations based on filters -- Aggregations on dates ( range, histogram ) -- Aggregations on numeric values (range, histogram) -- Aggregations on geolocation (distance, bounds) -- Geo distance -- Geo bounds -- Aggregations on child documents -- Aggregations on nested documents -- Reverse nested aggregation -- Post filter -- Using Kibana to visualize aggregations -- Caching -- Doc values -- Field data -- Summary -- Chapter 9: Production and Beyond -- Configuring Elasticsearch -- The directory structure -- zip/tar.gz -- DEB/RPM -- Configuration file -- Cluster and node name -- Network configuration -- Memory configuration -- Configuring file descriptors -- Types of nodes -- Multinode cluster -- Inspecting the logs -- How nodes discover each other -- Node failures -- X-Pack -- Windows -- Mac OS X -- Debian/RPM -- Authentication -- X-Pack basic license -- Monitoring -- Monitoring Elasticsearch clusters -- Monitoring indices -- Monitoring nodes -- Thread pools -- Elasticsearch server logs -- Slow logs -- Summary -- Chapter 10: Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting) -- Elastic Cloud -- High availability -- Data reliability -- Security -- Authentication and roles -- Securing communications using SSL -- Graph -- Graph UI -- Alerting -- Summary -- Index.

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