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# # Solr Features## Solr is an independent enterprise search server that provides API similar to REST. You can store documents (or indexes) through the binary of XML, JSON, CVS, or HTTP. You can query and accept XML, JSON, CVS or binary data through the HTTP GET method.

Advanced full-text retrieval function

Optimize for network traffic with high throughput

Based on open interface standards-XML, JSON and HTTP

Comprehensive HTML management interface

Server statistics are exposed, which can be monitored through JMX

Linear scalability, automatic index replication, automatic failover and recovery

Near real-time index

Flexibility and adaptability based on XML configuration

Extensible plug-in architecture

# Solr uses Lucene to retrieve the library and extend it #

A real data pattern, including numeric types, dynamic fields, unique keys

Powerful extension to Lucene query language

Aspect retrieval and filtering

Support geospatial retrieval of multipoints and geo-polygons in each document

Advanced, configurable text analyzer

Highly configurable and user scalable cach

Performance optimization

Scalable configuration based on XML

Management Interface based on AJAX

Logs that can be monitored

Fast and near-real-time incremental index and index replication

Highly scalable distributed retrieval based on index fragments across multiple hosts

JSON, XML, CVS/delimited-text, and binary update formats

A simple way to pull data from a database, a XML file on a local disk, or a HTTP resource

Use Apache Tika to parse and index rich text (PDF, Word, HTML, etc.)

Metadata extraction based on Apache UIMA Integrated configuration

Multiple retrieval index

# Schema####

Define document fields and specify field types

Can drive smarter processing

Declarative lucene word splitter

Dynamic fields are new fields that can be added immediately.

The field replication function allows multiple ways to index a single field, or to merge multiple fields into a single search field.

Explicit type that sorts the necessary guess field types

Configuration stop word list, synonym list, protection word list based on extended (external file) files

Many additional text analysis components, including word segmentation, regular expressions, and sounds-like filters

Each field has a pluggable similar model

# Query####

The HTTP interface provides configurable response formats (XML/XSLT, JSON, Python, Ruby, PHP, Velocity, CSV, binary)

Can be sorted by any number of fields or by complex functions for any number of fields

The advanced DisMax query analyzer obtains highly relevant results from queries entered by the user

Highlight context clip

Retrieval based on unique field values, explicit queries, date ranges, numeric ranges, or point aspects

Multifaceted retrieval through tags or optional execution filtering

Make spelling suggestions for user queries

Similarity suggestions for a given document

Function query-affects the score of a complex numeric field or query correlation score function specified by the user

Filter the range of results by function query

Range filter over Function Query results

Date Math-specify dates relative to "NOW" in queries and updates

Clustering dynamic search results by carrot2

Numeric field statistics, such as minimum, maximum, average, standard deviation

Combine queries derived from different syntaxes

Automatic suggestion function to complete user query

Allows you to configure the highest priority results of a query, which can override normal scores and sorting

Simply connect two document types

Performance optimization

# Core####

Dynamically create or delete a collection of documents without restarting the service

Pluggable query processor and extensible XML data format

Pluggable user function for function query

Customizable build-based request processor and support for distributed retrieval

Document uniqueness Enhancement based on unique key Field

Duplicate file detection, including fuzzy near duplicates

Customizable index processing chain that allows document processing before indexing

User configurable commands triggered on index changes

Ability to control where docs with the sort field missing will be placed

"Luke" request handler for corpus information

# SolrCloud####

Centralized configuration based on Apache ZooKeeper

Automatically distributed indexing / sharding, sending the document to any node and the document will be forwarded to the correct shard

Near real-time index based on immediate push model (which also supports slow pull model replication)

The transaction log ensures that even if the updated document is not indexed to disk, it will not be lost

Automatic index failover, index leader election, and failure recovery if failed

No single point of failure

# Admin Interface####

Comprehensive statistics on cache utilization, update, and query

Interactive mode browsing including index statistics

Replication monitoring

SolrCloud dashboard for graphical status of cluster nodes

Full log control

Text analysis and debugging, showing the analysis results of each stage of an analyzer

Web query interface, w / mode output

Parsed query output

Detailed Design of document score based on Lecene explain ()

Explain score for documents outside of the requested range to debug why a given document wasn't ranked highe

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