elasticsearch补全功能之只补全筛选后的部分数据context suggester

官方文档https://www.elastic.co/guide/en/elasticsearch/reference/5.0/suggester-context.html

　　下面所有演示基于elasticsearch5.x和Python3.x

　　最近项目使用elasticsearch的补全功能时，需要对于所有文章(article)的作者名字(author)的搜索做补全，文章的mapping大致如下

ARTICLE = {
    'properties': {
        'id': {
            'type': 'integer',
            'index': 'not_analyzed',
        },
        'author': {
            'type': 'text',
        },
        'author_completion': {
            'type': 'completion',
        },
        'removed': {
            'type': 'boolean',
        }
    }
}

MAPPINGS = {
    'mappings': {
        'article': ARTICLE,
    }
}

　　现在的需求是，针对于下架状态removed为True的不做补全提示。

　　作为演示先插入部分数据，代码如下

　　

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from elasticsearch.helpers import bulk
from elasticsearch import Elasticsearch

ES_HOSTS = [{'host': 'localhost', 'port': 9200}, ]

ES = Elasticsearch(hosts=ES_HOSTS)

INDEX = 'test_article'
TYPE = 'article'

ARTICLE = {
    'properties': {
        'id': {
            'type': 'integer',
            'index': 'not_analyzed',
        },
        'author': {
            'type': 'text',
        },
        'author_completion': {
            'type': 'completion',
        },
        'removed': {
            'type': 'boolean',
        }
    }
}

MAPPINGS = {
    'mappings': {
        'article': ARTICLE,
    }
}

def create_index():
    """
    插入数据前创建对应的index
    """
    ES.indices.delete(index=INDEX, ignore=404)
    ES.indices.create(index=INDEX, body=MAPPINGS)

def insert_data():
    """
    添加测试数据
    :return:
    """
    test_datas = [
        {
            'id': 1,
            'author': 'tom',
            'author_completion': 'tom',
            'removed': False
        },
        {
            'id': 2,
            'author': 'tom_cat',
            'author_completion': 'tom_cat',
            'removed': True
        },
        {
            'id': 3,
            'author': 'kitty',
            'author_completion': 'kitty',
            'removed': False
        },
        {
            'id': 4,
            'author': 'tomato',
            'author_completion': 'tomato',
            'removed': False
        },
    ]
    bulk_data = []
    for data in test_datas:
        action = {
            '_index': INDEX,
            '_type': TYPE,
            '_id': data.get('id'),
            '_source': data
        }
        bulk_data.append(action)

    success, failed = bulk(client=ES, actions=bulk_data, stats_only=True)

    print('success', success, 'failed', failed)

if __name__ == '__main__':
    create_index()
    insert_data()

　　成功插入4条测试数据，下面测试获取作者名称补全建议，代码如下

def get_suggestions(keywords):
    body = {
        # 'size': 0,  # 这里是不返回相关搜索结果的字段，如author,id等，作为测试这里返回
        '_source': 'suggest',
        'suggest': {
            'author_prefix_suggest': {
                'prefix': keywords,
                'completion': {
                    'field': 'author_completion',
                    'size': 10,
                }
            }
        },
        # 对于下架数据，我单纯的以为加上下面的筛选就行了
        'query': {
            'term': {
                'removed': False
            }
        }
    }
    suggest_data = ES.search(index=INDEX, doc_type=TYPE, body=body)
    return suggest_data

if __name__ == '__main__':
    # create_index()
    # insert_data()

    suggestions = get_suggestions('t')
    print(suggestions)
    """
    suggestions = {
        'took': 0,
        'timed_out': False,
        '_shards': {
            'total': 5,
            'successful': 5,
            'skipped': 0,
            'failed': 0
        },
        'hits': {
            'total': 3,
            'max_score': 0.6931472,
            'hits': [
                {'_index': 'test_article', '_type': 'article', '_id': '4', '_score': 0.6931472,
                 '_source': {}},
                {'_index': 'test_article', '_type': 'article', '_id': '1', '_score': 0.2876821,
                 '_source': {}},
                {'_index': 'test_article', '_type': 'article', '_id': '3', '_score': 0.2876821,
                 '_source': {}}]},
        'suggest': {
            'author_prefix_suggest': [{'text': 't', 'offset': 0, 'length': 1, 'options': [
                {'text': 'tom', '_index': 'test_article', '_type': 'article', '_id': '1', '_score': 1.0,
                 '_source': {}},
                {'text': 'tom_cat', '_index': 'test_article', '_type': 'article', '_id': '2', '_score': 1.0,
                 '_source': {}},
                {'text': 'tomato', '_index': 'test_article', '_type': 'article', '_id': '4', '_score': 1.0,
                 '_source': {}}]}]
        }
    }
    """

　　发现，removed为True的tom_cat赫然在列，明明加了

'query': {
            'term': {
                'removed': False
            }
        }

　　却没有起作用，难道elasticsearch不支持这种需求！？怎么可能……

　　查阅文档发现解决方法为https://www.elastic.co/guide/en/elasticsearch/reference/5.0/suggester-context.html

　　找到问题所在，首先改造mapping，并重新录入测试数据如下

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from elasticsearch.helpers import bulk
from elasticsearch import Elasticsearch

ES_HOSTS = [{'host': 'localhost', 'port': 9200}, ]

ES = Elasticsearch(hosts=ES_HOSTS)

INDEX = 'test_article'
TYPE = 'article'

ARTICLE = {
    'properties': {
        'id': {
            'type': 'integer',
            'index': 'not_analyzed'
        },
        'author': {
            'type': 'text',
        },
        'author_completion': {
            'type': 'completion',
            'contexts': [  # 这里是关键所在
                {
                    'name': 'removed_tab',
                    'type': 'category',
                    'path': 'removed'
                }
            ]
        },
        'removed': {
            'type': 'boolean',
        }
    }
}

MAPPINGS = {
    'mappings': {
        'article': ARTICLE,
    }
}

def create_index():
    """
    插入数据前创建对应的index
    """
    ES.indices.delete(index=INDEX, ignore=404)
    ES.indices.create(index=INDEX, body=MAPPINGS)

def insert_data():
    """
    添加测试数据
    :return:
    """
    test_datas = [
        {
            'id': 1,
            'author': 'tom',
            'author_completion': 'tom',
            'removed': False
        },
        {
            'id': 2,
            'author': 'tom_cat',
            'author_completion': 'tom_cat',
            'removed': True
        },
        {
            'id': 3,
            'author': 'kitty',
            'author_completion': 'kitty',
            'removed': False
        },
        {
            'id': 4,
            'author': 'tomato',
            'author_completion': 'tomato',
            'removed': False
        },
    ]
    bulk_data = []
    for data in test_datas:
        action = {
            '_index': INDEX,
            '_type': TYPE,
            '_id': data.get('id'),
            '_source': data
        }
        bulk_data.append(action)

    success, failed = bulk(client=ES, actions=bulk_data, stats_only=True)

    print('success', success, 'failed', failed)

if __name__ == '__main__':
    create_index()
    insert_data()

　　Duang！意想不到的问题出现了

elasticsearch.helpers.BulkIndexError: ('4 document(s) failed to index.', [{'index': {'_index': 'test_article', '_type': 'article', '_id': '1', 'status': 400, 'error': {'type': 'illegal_argument_exception', 'reason': 'Failed to parse context field [removed], only keyword and text fields are accepted'}, 'data': {'id': 1, 'author': 'tom', 'author_completion': 'tom', 'removed': False}}}, {'index': {'_index': 'test_article', '_type': 'article', '_id': '2', 'status': 400, 'error': {'type': 'illegal_argument_exception', 'reason': 'Failed to parse context field [removed], only keyword and text fields are accepted'}, 'data': {'id': 2, 'author': 'tom_cat', 'author_completion': 'tom_cat', 'removed': True}}}, {'index': {'_index': 'test_article', '_type': 'article', '_id': '3', 'status': 400, 'error': {'type': 'illegal_argument_exception', 'reason': 'Failed to parse context field [removed], only keyword and text fields are accepted'}, 'data': {'id': 3, 'author': 'kitty', 'author_completion': 'kitty', 'removed': False}}}, {'index': {'_index': 'test_article', '_type': 'article', '_id': '4', 'status': 400, 'error': {'type': 'illegal_argument_exception', 'reason': 'Failed to parse context field [removed], only keyword and text fields are accepted'}, 'data': {'id': 4, 'author': 'tomato', 'author_completion': 'tomato', 'removed': False}}}])

　　意思是context只支持keyword和text类型，而上面removed类型为boolean，好吧，再改造mapping，将mapping的removed改为keyword类型……

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from elasticsearch.helpers import bulk
from elasticsearch import Elasticsearch

ES_HOSTS = [{'host': 'localhost', 'port': 9200}, ]

ES = Elasticsearch(hosts=ES_HOSTS)

INDEX = 'test_article'
TYPE = 'article'

ARTICLE = {
    'properties': {
        'id': {
            'type': 'integer',
            'index': 'not_analyzed'
        },
        'author': {
            'type': 'text',
        },
        'author_completion': {
            'type': 'completion',
            'contexts': [  # 这里是关键所在
                {
                    'name': 'removed_tab',
                    'type': 'category',
                    'path': 'removed'
                }
            ]
        },
        'removed': {
            'type': 'keyword',
        }
    }
}

MAPPINGS = {
    'mappings': {
        'article': ARTICLE,
    }
}

def create_index():
    """
    插入数据前创建对应的index
    """
    ES.indices.delete(index=INDEX, ignore=404)
    ES.indices.create(index=INDEX, body=MAPPINGS)

def insert_data():
    """
    添加测试数据
    :return:
    """
    test_datas = [
        {
            'id': 1,
            'author': 'tom',
            'author_completion': 'tom',
            'removed': 'False'
        },
        {
            'id': 2,
            'author': 'tom_cat',
            'author_completion': 'tom_cat',
            'removed': 'True'
        },
        {
            'id': 3,
            'author': 'kitty',
            'author_completion': 'kitty',
            'removed': 'False'
        },
        {
            'id': 4,
            'author': 'tomato',
            'author_completion': 'tomato',
            'removed': 'False'
        },
    ]
    bulk_data = []
    for data in test_datas:
        action = {
            '_index': INDEX,
            '_type': TYPE,
            '_id': data.get('id'),
            '_source': data
        }
        bulk_data.append(action)

    success, failed = bulk(client=ES, actions=bulk_data, stats_only=True)

    print('success', success, 'failed', failed)

if __name__ == '__main__':
    create_index()
    insert_data()

　　mission success。看看表结构ok

接下来就是获取补全建议

def get_suggestions(keywords):
    body = {
        'size': 0,
        '_source': 'suggest',
        'suggest': {
            'author_prefix_suggest': {
                'prefix': keywords,
                'completion': {
                    'field': 'author_completion',
                    'size': 10,
                    'contexts': {
                        'removed_tab': ['False', ]  # 筛选removed为'False'的补全，contexts不能包含多个tab，如加上一个'state_tab':['1',]的话contexts将失效
                    }
                }
            }
        },
    }
    suggest_data = ES.search(index=INDEX, doc_type=TYPE, body=body)
    return suggest_data

if __name__ == '__main__':
    # create_index()
    # insert_data()
    suggestions = get_suggestions('t')
    print(suggestions)

    """
    suggestions = {
        'took': 0,
        'timed_out': False,
        '_shards': {
            'total': 5,
            'successful': 5,
            'skipped': 0, 'failed': 0
        },
        'hits': {
            'total': 0,
            'max_score': 0.0,
            'hits': []
        },
        'suggest': {
            'author_prefix_suggest': [
                {'text': 't', 'offset': 0, 'length': 1, 'options': [
                    {'text': 'tom', '_index': 'test_article', '_type': 'article', '_id': '1', '_score': 1.0,
                     '_source': {},
                     'contexts': {'removed_tab': ['False']}},
                    {'text': 'tomato', '_index': 'test_article', '_type': 'article', '_id': '4', '_score': 1.0,
                     '_source': {},
                     'contexts': {'removed_tab': ['False']}}]}]}}
        """

　　发现，removed为'True'的tom_cat被筛选掉了，大功告成！