A, aboutElasticsearchThe understanding of the

  • What is Elasticsearch

    ElasticSearch is a Lucene-based search server. It provides a distributed multi – user – capable full – text search engine based on RESTful Web interface. Elasticsearch, developed in Java and released as open source under the Apache license, is a popular enterprise-level search engine. Designed for use in cloud computing, real-time search is possible. Stable, reliable, fast, easy to install and use.

    ElasticSearch is a Restful interface based database similar to mysql and more specifically mongodb document database

  • 2. Several ways to search for data

    • Direct use ofmysqltheLIKEFuzzy query (not recommended)
    • Full-text search using databases (slow search)
    • useElasticSearch

Second, about theElasticSearchSeveral concepts in

  • Cluster (cluster)

    Represents a cluster in which there are multiple nodes, one of which is the primary node, which is elected (the primary and secondary nodes are within the cluster). One concept of ElasticSearch is decentralization, which literally means node-less. This is for the outside of the cluster, because the ElasticSearch cluster is logically whole from the outside, and your communication with any one node is equivalent to that with the entire ES cluster.

  • The index (index)

    You can create one or more indexes in ElasticSearch. We can write documents to or read documents from an index (metaphorically, we can insert and read data from a database)

  • The document (the document)

    A document can be understood simply as a table in a database, which is the entity on which ElasticSearch ultimately operates

  • Mapping (mapping)

    Plain documents are analyzed before being indexed. How do you separate the input text into terms and which terms are filtered, a practice called mapping

  • Type (type)

    Each document has a corresponding type, which allows users to store multiple document types in a single index without providing different document types and different mappings

  • Shard (shards)

    ElasticSearch can split a complete index into multiple shards. This allows you to split a large index into multiple shards and distribute them on different nodes. Constitute a distributed search. The number of shards can only be specified before the index is created, and cannot be changed after the index is created

Three,dockerThe installationElasticsearch

  • 1. Install the image of the latest version directly

    docker pull elasticsearch
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  • 2. Start the image

    docker run --name elasticsearch -d -e ES_JAVA_OPTS="-Xms512m -Xmx512m" -e "discovery.type=single-node" -p 9200:9200 -p 9300:9300 elasticsearch
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  • 3. Enter the browser to test whether the container is successfully started

    http://localhost:9200
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    {
  name: "N9kE1aI",
  cluster_name: "elasticsearch",
  cluster_uuid: "4B0Z7qa2QjSbsRB1JMTZzw",
  version: {
    number: "5.6.12."
    build_hash: "cfe3d9f",
    build_date: "The 2018-09-10 T20: when 732 z",
    build_snapshot: false,
    lucene_version: "6.6.1"
  },
  tagline: "You Know, for Search"
}
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  • 4. Deal with cross-domain issues

    # Enter the container
docker Exec it [container ID] /bin/bash
Go to the directory
cd config
Write file
echo 'http.cors.allow-origin: "*"' >> elasticsearch.yml
echo "http.cors.enabled: true" >> elasticsearch.yml
# View file contents
cat elasticsearch.yml
# Exit container
exit
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  • 5. Restart the container

    docker Restart [container ID]
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4. Install Chinese word segmentation plug-in

  • 1. Official website address

  • 2. Download address

  • 3. Copy the downloaded file to the Docker container

    docker Cp/directory/elasticsearch - analysis - ik - 7.11.2. Zip container ID: / usr/share/elasticsearch/plugins
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  • 4. Enter the container

  • 5, in the/usr/share/elasticsearch/plugins/directory to create a folder ik, and move the word segmentation software just copy to ik directory

    # create file
mkdir ik
# move file
mv Elasticsearch - analysis - ik - 7.11.2.zip ik
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  • 6. Unzip and delete files

    unzip Elasticsearch - analysis - ik - 7.11.2. Zip
Delete the compressed package
rm - rf elasticsearch - analysis - ik - 7.11.2. Zip
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  • 7. Exit the container and restart it.

  • Docker elasticSearch is not the same as docker elasticSearch

    • View the ElasticSearch version

      # Check the version of ElasticSearch that is already installed
docker image inspect elasticsearch:latest | grep -i version
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      "JAVA_VERSION=8u181",
"JAVA_DEBIAN_VERSION=8u181-b13-1~deb9u1",
"CA_CERTIFICATES_JAVA_VERSION=20170531+nmu1",
"GOSU_VERSION=1.10 ",
"ELASTICSEARCH_VERSION=5.6.12."
"ELASTICSEARCH_DEB_VERSION=5.6.12. ""
"DockerVersion": "17.06.2 - ce",
"JAVA_VERSION=8u181",
"JAVA_DEBIAN_VERSION=8u181-b13-1~deb9u1",
"CA_CERTIFICATES_JAVA_VERSION=20170531+nmu1",
"GOSU_VERSION=1.10 ",
"ELASTICSEARCH_VERSION=5.6.12."
"ELASTICSEARCH_DEB_VERSION=5.6.12. ""
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    • Install the Vim editor

      apt-get update
apt-get install vim
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    • Go to ElasticSearch and change the version of the elasticSearch plug-in

      # Edit file
vim plugin-descriptor.properties
The modified version corresponds to it
elasticsearch.version=5.6.12
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    • Restart the container

  • Or you can download the version of ElasticSearch by checking the Chinese word segmentation plugin you downloaded

5. Install the client visualization tool

  • Install mobz/ ElasticSearch-head using Docker

    docker pull mobz/elasticsearch-head:5
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  • 2. Start the container

    docker run -d -p 9100:9100 docker.io/mobz/elasticsearch-head:5
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  • Elasticsearch will automatically connect to your browser

    http://localhost:9100/
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  • 4, create index

6, create index exception processing

  • 1. When you click create index and nothing happens, open your browser console and check

  • 2, Go to the mobz/ ElasticSearch-head container and modify the code

    docker Exec-it Container ID /bin/bash
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  • 3. Modify the /usr/src/app/_site/vendor.js file

    # Update package
apt-get update
# install vim
apt-get install vim
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  • 4, modify code 1 (look at line number)

    # code
contentType: "application/x-www-form-urlencoded
# modified to
contentType: "application/json; charset=UTF-8"
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  • 5, modify the code and (look at the line number)

    # code
var inspectData = s.contentType === "application/x-www-form-urlencoded" &&
# modified to
var inspectData = s.contentType === "application/json; charset=UTF-8" &&
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  • 6. Restart the container

    docker Restart the container ID
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