“It is an interesting story and dates back half a century. This is a Rare Course and it can be take up to 3 weeks to arrange the training. Searching, indexing, Faceting and HighlightersĪpache Solr Cloud configuration for distributed indexing and search Understand scalable, fault-tolerant features of Solr Learn the concepts of Apache Solr and its advantages Indexing and Searching with Apache Lucene library Upon completion of this course, participants will learn the following: This will also cover advanced topics like Spellcheck and search suggestions. Post fundamental concepts it will cover use cases of Solr, internal Architecture, Components, Highlighters, Faceting, Solr Cloud, Solr Admin. It starts with fundamental concepts like searching text using Lucene, Lucene components like Solr Installation, Analyzers, Searchers, Indexing & Updating schemas and Faceting. This course is designed to make the participants experts in Apache Solr (Search engine). Major features include full-text search, hit highlighting, faceted search. Streaming Expressions: A stream processing language for Solr, with a suite of functions to perform many types of queries and parallel execution tasks.Ĭlient APIs: This section tells you how to access Solr through various client APIs, including JavaScript, JSON, and Ruby.Enroll for the 3-days Apache Solr training and certification course from Koenig solutions.Īpache Solr based on the Lucene Library, is an open-source enterprise Grade search engine and platform used to provide fast and scalable search features. It lists the query parameters that can be passed to Solr, and it describes features such as boosting and faceting, which can be used to fine-tune search results. It describes the main components used in searches, including request handlers, query parsers, and response writers. Searching: This section presents an overview of the search process in Solr. Filters perform other transformational or selective work on token streams. Tokenizers break field data down into tokens. Analyzers parse text and produce a stream of tokens, lexical units used for indexing and searching. Understanding Analyzers, Tokenizers, and Filters: This section explains how Solr prepares text for indexing and searching. It explains how a Solr schema defines the fields and field types which Solr uses to organize data within the document files it indexes. Indexing and Basic Data Operations: This section describes the indexing process and basic index operations, such as commit, optimize, and rollback.ĭocuments, Fields, and Schema Design: This section describes how Solr organizes data in the index.
0 Comments
Leave a Reply. |