What is the role of solr in docker?

In docker, solr represents an open source search platform, used to build search applications; XML files in a certain format can be submitted to the search engine server through http requests to generate indexes, or searches can be made through the "Http Get" operation. Request and get the returned result in XML format.

The operating environment of this tutorial: linux7.3 system, docker-1.13.1 version, Dell G3 computer.

What is the role of solr in docker

Solr is an open source search platform used to build search applications. It is built on top of Lucene (full text search engine). Solr is enterprise-grade, fast and highly scalable. Applications built with Solr are highly complex and deliver high performance.

You can submit an XML file in a certain format to the search engine server through http requests to generate an index; you can also make a search request through Http Get operations and get the returned results in XML format.

Deploy Solr and install IKAnalyzer

Write yml file

version: '3.1'
services:
  solr:
    build: ikanalyzer
    restart: always
    container_name: solr
    ports:
      - 8983:8983
    volumes:
      - ./solrdata:/opt/solrdata

Dockerfile

FROM solr:7.1.0
# 创建 Core
WORKDIR /opt/solr/server/solr
RUN mkdir ik_core
WORKDIR /opt/solr/server/solr/ik_core
RUN echo 'name=ik_core' > core.properties
RUN mkdir data
RUN cp -r ../configsets/sample_techproducts_configs/conf/ .
# 安装中文分词
WORKDIR /opt/solr/server/solr-webapp/webapp/WEB-INF/lib
ADD ik-analyzer-solr5-5.x.jar .
ADD solr-analyzer-ik-5.1.0.jar .
WORKDIR /opt/solr/server/solr-webapp/webapp/WEB-INF
ADD ext.dic .
ADD stopword.dic .
ADD IKAnalyzer.cfg.xml .
# 增加分词配置
COPY managed-schema /opt/solr/server/solr/ik_core/conf
WORKDIR /opt/solr

Solr is a high-performance, Java-developed, Lucene-based full-text search server. At the same time, it has been extended to provide a richer query language than Lucene. It is also configurable, scalable and optimized for query performance. It also provides a complete function management interface. It is a very excellent Full-text search engine

Documents are added to a search collection via HTTP using XML. Querying the collection is also achieved by receiving an XML/JSON response via http. Its main features include: efficient and flexible caching function, vertical search function, highlighting search results, improving usability through index replication, providing a set of powerful Data Schema to define fields, types and settings for text analysis, and providing Web-based Management interface, etc.

Recommended learning: "docker video tutorial"

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