[英]Use python to get data table Visualization from elastic search
How can I filter and summarize data in elastic search through python. 如何通过python在弹性搜索中过滤和汇总数据。 I manually created a data table visualization through Kibana interface and downloaded it in .csv format.
我通过Kibana界面手动创建了数据表可视化,并以.csv格式下载了它。 Now I want to do the same using python.
现在我想使用python做同样的事情。
For example, if there are 10 variables in the index: v1,v2,v3,.. v10
then how to get a data table which can be described in sql as: 例如,如果索引中有10个变量:
v1,v2,v3,.. v10
则如何获取数据表,该数据表可以在sql中描述为:
select v2, count(v2)
from index
where v1 = "some value"
group by v2
Till now I am able to do this: 到现在为止,我可以执行以下操作:
from elasticsearch5 import Elasticsearch
user = 'xxx'
password = 'xxx'
url = 'xxx'
command = "%s:%s@%s:9200" % (user,password,url)
x = Elasticsearch(command)
# Get the count of documents
num = x.count(index='my_index')['count']
# Get documents filtered by v1
my_docs = x.search(index="my_index", body={"query": {"match": {'v1':'US'}}})
Now what I want is to select only variable v2
from my_docs and also group by v2
to get a count. 现在,我要从my_docs中仅选择变量
v2
,并按v2
分组以获得计数。 Apologies that I don't know how to create a reproducible example without revealing the user credentials. 在不透露用户凭据的情况下我不知道如何创建可复制示例的道歉。
If you want to treat only few fields on your doc, you should use the _source filter
before your query - doc here . 如果您只想处理文档中的少数几个字段,则应在此处查询doc之前使用
_source filter
。 For example to retrieve from your docs only the v1
and v2
fields : 例如,仅从文档中检索
v1
和v2
字段:
body={
"_source": ["v1", "v2"],"query": {"match": {'v1':'US'}}}
You just try something like this: 您只需尝试如下操作:
for result in mydocs['hits']['hits']:
print result["_source"]['v1']
print result["_source"]['v2']
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