Elasticsearch入門

elasticsearch使用--簡單入門(一)

一、下載安裝

  • 安裝java
  • 下載elasticsearch相應版本
  • 啟動

二、瀏覽集群

1、使用REST API

  1. Check your cluster, node, and index health, status, and statistics
  2. Administer your cluster, node, and index data and metadata
  3. Perform CRUD (Create, Read, Update, and Delete) and search operations against your indexes
  4. Execute advanced search operations such as paging, sorting, filtering, scripting, aggregations, and many others

2、查看集群的健康程度

curl 'localhost:9200/_cat/health?v'

3、列出集群中所有的節點

curl 'localhost:9200/_cat/nodes?v'

4、列出所有的index

curl 'localhost:9200/_cat/indices?v'

5、創建index

curl -XPUT 'localhost:9200/customer?pretty'

The first command creates the index named "customer" using the PUT verb. We simply append pretty to the end of the call to tell it to pretty-print the JSON response (if any).

6、索引和查找一個document

索引

Let’s index a simple customer document into the customer index, "external" type, with an ID of 1 as follows:
Our JSON document: { "name": "John Doe" }

curl -XPUT 'localhost:9200/customer/external/1?pretty' -d ' { "name": "John Doe" }'

查找

curl -XGET 'localhost:9200/customer/external/1?pretty'

7、刪除一個index

curl -XDELETE 'localhost:9200/customer?pretty'

If we study the above commands carefully, we can actually see a pattern of how we access data in Elasticsearch. That pattern can be summarized as follows:

curl -X<REST Verb> <Node>:<Port>/<Index>/<Type>/<ID>

二、修改數據

1、indexing and replacing data

一個簡單的例子

curl -XPUT 'localhost:9200/customer/external/1?pretty' -d '
 {
   "name": "John Doe"
 }'`

curl -XPUT 'localhost:9200/customer/external/1?pretty' -d '
 {
   "name": "Jane Doe"
 }'

This example shows how to index a document without an explicit ID:

curl -XPOST 'localhost:9200/customer/external?pretty' -d '
{
  "name": "Jane Doe"
}'

Note that in the above case, we are using the POST verb instead of PUT since we didn’t specify an ID.

2、更新documents

Note though that Elasticsearch does not actually do in-place updates under the hood. Whenever we do an update, Elasticsearch deletes the old document and then indexes a new document with the update applied to it in one shot.

This example shows how to update our previous document (ID of 1) by changing the name field to "Jane Doe":

curl -XPOST 'localhost:9200/customer/external/1/_update?pretty' -d '
{
  "doc": { "name": "Jane Doe" }
}'

This example shows how to update our previous document (ID of 1) by changing the name field to "Jane Doe" and at the same time add an age field to it:

curl -XPOST 'localhost:9200/customer/external/1/_update?pretty' -d '
{
  "doc": { "name": "Jane Doe", "age": 20 }
}'

Updates can also be performed by using simple scripts.This example uses a script to increment the age by 5:

curl -XPOST 'localhost:9200/customer/external/1/_update?pretty' -d '
{
  "script" : "ctx._source.age += 5"
}'

In the above example, ctx._source refers to the current source document that is about to be updated.

Note that as of this writing, updates can only be performed on a single document at a time.

3、刪除document

This example shows how to delete our previous customer with the ID of 2:

curl -XDELETE 'localhost:9200/customer/external/2?pretty'

The delete-by-query plugin can delete all documents matching a specific query.

4、批處理

As a quick example, the following call indexes two documents (ID 1 - John Doe and ID 2 - Jane Doe) in one bulk operation:

curl -XPOST 'localhost:9200/customer/external/_bulk?pretty' -d '
{"index":{"_id":"1"}}
{"name": "John Doe" }
{"index":{"_id":"2"}}
{"name": "Jane Doe" }
'

This example updates the first document (ID of 1) and then deletes the second document (ID of 2) in one bulk operation:

curl -XPOST 'localhost:9200/customer/external/_bulk?pretty' -d '
{"update":{"_id":"1"}}
{"doc": { "name": "John Doe becomes Jane Doe" } }
{"delete":{"_id":"2"}}'

Note above that for the delete action, there is no corresponding source document after it since deletes only require the ID of the document to be deleted.

bulk API按照順序執行每一條語句，如果其中一條語句失敗了，仍然會繼續執行下去。執行完成之后，會按照順序返回每一條語句執行后的狀態。

三、瀏覽數據

1、Sample Dataset

curl -XPOST 'localhost:9200/bank/account/_bulk?pretty' --data-binary "@accounts.json"

2、Search API

Now let’s start with some simple searches. There are two basic ways to run searches: one is by sending search parameters through the REST request URI and the other by sending them through the REST request body.

The REST API for search is accessible from the _search endpoint. This example returns all documents in the bank index:

curl 'localhost:9200/bank/_search?q=*&pretty'

Here is the same exact search above using the alternative request body method:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_all": {} }
}'

3、Query Language

es提供了一個json形式的面向domain的查詢語言。

In addition to the query parameter, we also can pass other parameters to influence the search results. For example, the following does a match_all and returns only the first document:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_all": {} },
  "size": 1
}'

Note that if size is not specified, it defaults to 10.

This example does a match_all and returns documents 11 through 20:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_all": {} },
  "from": 10,
  "size": 10
}'

Note that if from is not specified, it defaults to 0.

This example does a match_all and sorts the results by account balance in descending order and returns the top 10 (default size) documents.

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_all": {} },
  "sort": { "balance": { "order": "desc" } }
}'

4、執行查詢

This example shows how to return two fields, account_number and balance (inside of _source), from the search:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_all": {} },
  "_source": ["account_number", "balance"]
}'

This example returns the account numbered 20:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "account_number": 20 } }
}'

This example returns all accounts containing the term "mill" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "address": "mill" } }
}'

This example returns all accounts containing the term "mill" or "lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "address": "mill lane" } }
}'

This example is a variant of match (match_phrase) that returns all accounts containing the phrase "mill lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_phrase": { "address": "mill lane" } }
}'

This example composes two match queries and returns all accounts containing "mill" and "lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

In contrast, this example composes two match queries and returns all accounts containing "mill" or "lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "should": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

This example composes two match queries and returns all accounts that contain neither "mill" nor "lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must_not": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

This example returns all accounts of anybody who is 40 years old but don’t live in ID(aho):

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must": [
        { "match": { "age": "40" } }
      ],
      "must_not": [
        { "match": { "state": "ID" } }
      ]
    }
  }
}'

5、執行過濾器

過濾器不會影響到score字段。

一個例子：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must": { "match_all": {} },
      "filter": {
        "range": {
          "balance": {
            "gte": 20000,
            "lte": 30000
          }
        }
      }
    }
  }
}'

6、執行聚合

Aggregations provide the ability to group and extract statistics from your data.he easiest way to think about aggregations is by roughly equating it to the SQL GROUP BY and the SQL aggregate functions.

In Elasticsearch, you have the ability to execute searches returning hits and at the same time return aggregated results separate from the hits all in one response.

To start with, this example groups all the accounts by state, and then returns the top 10 (default) states sorted by count descending (also default):

 curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state"
      }
    }
  }
}'

Note that we set size=0 to not show search hits because we only want to see the aggregation results in the response.

Building on the previous aggregation, this example calculates the average account balance by state (again only for the top 10 states sorted by count in descending order):

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state"
      },
      "aggs": {
        "average_balance": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  }
}'

聚合可以嵌套使用。

Building on the previous aggregation, let’s now sort on the average balance in descending order:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state",
        "order": {
          "average_balance": "desc"
        }
      },
      "aggs": {
        "average_balance": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  }
}'
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