Elastic{ON}北京分享了Elasticsearch7.0在Speed,Scale,Relevance等方面的很多新特性。

elasticsearch体验——在windows10上安装配置以及插件安装配置

elasticsearch-head 安装介绍

双击执行 elasticsearch.bat，该脚本文件执行 ElasticSearch 安装程序
【注意，也可以在启动时设置一些参数，比如
.\bin\elasticsearch.bat -Ecluster.name=my_cluster -Enode.name=node_1】
打开浏览器，输入 http://localhost:9200 ，显式以下画面，说明ES安装成功。

启动后发觉，有段时间elasticsearch还是很吃内存的，大概2G。几分钟后貌似一切恢复正常。
*还需要注意的是，使用过程中该bat运行的cmd窗口不能关闭。
想在后台启动，则需要运行elasticsearch-service.bat将其安装为后台服务。安装为服务之后可以使用elasticsearch-service-mgr.exe进行界面管理。

启动 elasticsearch-head

在 elasticsearch-head 目录下，执行命令：

grunt server

Elasticsearch+Hbase实现海量数据秒回查询

>>> from elasticsearch import Elasticsearch
>>> es = Elasticsearch()
>>> es.indices.create(index='news', ignore=400)
{'acknowledged': True, 'shards_acknowledged': True, 'index': 'news'}
>>> data = {'title': '美国留给伊拉克的是个烂摊子吗', 'url': 'http://view.news.qq.com/zt2011/usa_iraq/index.htm'}
>>> result = es.create(index='news', doc_type='politics', id=1, body=data)
>>> print(result)
{'_index': 'news', '_type': 'politics', '_id': '1', '_version': 1, 'result': 'created', '_shards': {'total': 2, 'successful': 1, 'failed': 0}, '_seq_no': 0, '_primary_term': 1}

class Elasticsearch(object):"""Elasticsearch low-level client. Provides a straightforward mapping fromPython to ES REST endpoints.The instance has attributes ``cat``, ``cluster``, ``indices``, ``ingest``,``nodes``, ``snapshot`` and ``tasks`` that provide access to instances of:class:`~elasticsearch.client.CatClient`,:class:`~elasticsearch.client.ClusterClient`,:class:`~elasticsearch.client.IndicesClient`,:class:`~elasticsearch.client.IngestClient`,:class:`~elasticsearch.client.NodesClient`,:class:`~elasticsearch.client.SnapshotClient` and:class:`~elasticsearch.client.TasksClient` respectively. This is thepreferred (and only supported) way to get access to those classes and theirmethods.You can specify your own connection class which should be used by providingthe ``connection_class`` parameter::# create connection to localhost using the ThriftConnectiones = Elasticsearch(connection_class=ThriftConnection)If you want to turn on :ref:`sniffing` you have several options (describedin :class:`~elasticsearch.Transport`)::# create connection that will automatically inspect the cluster to get# the list of active nodes. Start with nodes running on 'esnode1' and# 'esnode2'es = Elasticsearch(['esnode1', 'esnode2'],# sniff before doing anythingsniff_on_start=True,# refresh nodes after a node fails to respondsniff_on_connection_fail=True,# and also every 60 secondssniffer_timeout=60)Different hosts can have different parameters, use a dictionary per node tospecify those::# connect to localhost directly and another node using SSL on port 443# and an url_prefix. Note that ``port`` needs to be an int.es = Elasticsearch([{'host': 'localhost'},{'host': 'othernode', 'port': 443, 'url_prefix': 'es', 'use_ssl': True},])If using SSL, there are several parameters that control how we deal withcertificates (see :class:`~elasticsearch.Urllib3HttpConnection` fordetailed description of the options)::es = Elasticsearch(['localhost:443', 'other_host:443'],# turn on SSLuse_ssl=True,# make sure we verify SSL certificatesverify_certs=True,# provide a path to CA certs on diskca_certs='/path/to/CA_certs')SSL client authentication is supported(see :class:`~elasticsearch.Urllib3HttpConnection` fordetailed description of the options)::es = Elasticsearch(['localhost:443', 'other_host:443'],# turn on SSLuse_ssl=True,# make sure we verify SSL certificatesverify_certs=True,# provide a path to CA certs on diskca_certs='/path/to/CA_certs',# PEM formatted SSL client certificateclient_cert='/path/to/clientcert.pem',# PEM formatted SSL client keyclient_key='/path/to/clientkey.pem')Alternatively you can use RFC-1738 formatted URLs, as long as they are notin conflict with other options::es = Elasticsearch(['http://user:secret@localhost:9200/','https://user:secret@other_host:443/production'],verify_certs=True)By default, `JSONSerializer<https://github.com/elastic/elasticsearch-py/blob/master/elasticsearch/serializer.py#L24>`_is used to encode all outgoing requests.However, you can implement your own custom serializer::from elasticsearch.serializer import JSONSerializerclass SetEncoder(JSONSerializer):def default(self, obj):if isinstance(obj, set):return list(obj)if isinstance(obj, Something):return 'CustomSomethingRepresentation'return JSONSerializer.default(self, obj)es = Elasticsearch(serializer=SetEncoder())"""def __init__(self, hosts=None, transport_class=Transport, **kwargs):""":arg hosts: list of nodes we should connect to. Node should be adictionary ({"host": "localhost", "port": 9200}), the entire dictionarywill be passed to the :class:`~elasticsearch.Connection` class askwargs, or a string in the format of ``host[:port]`` which will betranslated to a dictionary automatically.  If no value is given the:class:`~elasticsearch.Urllib3HttpConnection` class defaults will be used.:arg transport_class: :class:`~elasticsearch.Transport` subclass to use.:arg kwargs: any additional arguments will be passed on to the:class:`~elasticsearch.Transport` class and, subsequently, to the:class:`~elasticsearch.Connection` instances."""self.transport = transport_class(_normalize_hosts(hosts), **kwargs)# namespaced clients for compatibility with API namesself.indices = IndicesClient(self)self.ingest = IngestClient(self)self.cluster = ClusterClient(self)self.cat = CatClient(self)self.nodes = NodesClient(self)self.remote = RemoteClient(self)self.snapshot = SnapshotClient(self)self.tasks = TasksClient(self)self.xpack = XPackClient(self)

深入详解Elasticsearch

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