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Explain Faceting in Solr.?
As the name suggests, Faceting is the arrangement and categorization of all search results based on their index terms. The process of faceting makes the searching task smoother as users can look for the exact results.
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What is Apache Lucene?
Supported by Apache Software Foundation, Apache Lucene is a free, open-source, high-performance text search engine library written in Java by Doug Cutting. Lucence facilitates full-featured searching, highlighting, indexing and spellchecking of documents in various formats like MS Office docs, HTML, PDF, text docs and others.
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What file contains definition of the field types and fields of documents?
schema.xml file contains definitions of the field types and fields of documents.
2 What data is specified by Schema?
What is Apache Solr?
Apache Solr is a standalone full-text search platform to perform searches on multiple websites and index documents using XML and HTTP. Built on a Java Library called Lucence, Solr supports a rich schema specification for a wide range and offers flexibility in dealing with different document fields. It also consists of an extensive search plugin API for developing custom search behavior.
Top Answers to Solr Interview Questions
| Criteria | Solr | ElasticSearch |
| Data varieties | JSON, XML, CSV | JSON |
| Data de duplication | Supported | Not supported |
| Updates | Through configuration changes | Through custom work |
What file contains configuration for data directory?
Solrconfig.xml file contains configuration for data directory.
1 What is the use of stats.field?
It is used to generate statistics over the results of arbitrary numeric functions.
What command is used to see how to use the bin/Solr script?
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2 Which syntax is used to stop Solr?
Solr is shut down from the same terminal where it was launched. Click Ctrl+C to shut it down.
1 What is Highlighting?
Highlighting refers to the fragmentation of documents matching the user’s query included in the query response. These fragments are then highlighted and placed in a special section, which is used by clients and users to present the snippets. Solr consists of a number of highlighting utilities having control over different fields. The highlighting utilities can be called by Request Handlers and reused with standard query parsers.
1 What is copying field?
It is used to describe how to populate fields with data copied from another field.
2 Name the basic Field types in Solr?
Become Master of Apache Solr by going through this online Solr Training.
Q. Define the Highlighting in Apache Solr? Here, documents will be fragmented to match the query response of the users, and search results become more accurate when the query is performed on small sections instead of the whole document. Solr has a variety of highlighting utilities that help to make solid control over different fields. The different utilities are used by Request Handlers and they are used again by Apache Lucene Parser or Standard query parser to process a series of token or fragmented documents.
Working with textual data in Solr, Field Analyzer reviews and checks the filed text and generates a token stream. The pre-process of analyzing of the input text is performed at the time of searching or indexing and at query time. Most Solr applications use Custom Analyzers defined by users. Remember, each Analyzer has only one Tokenizer. You can define an analyzer in the application using the below syntax:
Q. What are Necessary Details Included for “Field type” in Apache Solr? Every time you create a new field in Apache Solr, it should be given a proper Field name, define the field attributes, an implementation class, and given a brief field description.
Q. Explain the Concept of Dynamic Fields in Solr? In case, users forgot to define some necessary fields then dynamic fields are just the perfect choice to consider. You can create multiple dynamic fields together and they are highly flexible in indexing fields that are not explicitly defined in the schema.
A tokenizer receives a stream of characters, breaks it up into individual tokens (usually individual words), and outputs a stream of tokens. Inverted indexes are created and updates using these token values by recording the order or position of each term and the start and end character offsets of the original word which the term represents.