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elasticsearch-dbapi-0.2.9
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مشاهده بیشترتوضیحات
A DBAPI and SQLAlchemy dialect for Elasticsearch
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | elasticsearch-dbapi-0.2.9 |
| نام | elasticsearch-dbapi |
| نسخه کتابخانه | 0.2.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Preset Inc. |
| ایمیل نویسنده | daniel@preset.io |
| آدرس صفحه اصلی | http://preset.io |
| آدرس اینترنتی | https://pypi.org/project/elasticsearch-dbapi/ |
| مجوز | Apache License, Version 2.0 |
# ElasticSearch DBAPI
[](https://github.com/preset-io/elasticsearch-dbapi/actions)
[](https://badge.fury.io/py/elasticsearch-dbapi)
[](https://codecov.io/github/preset-io/elasticsearch-dbapi)
`elasticsearch-dbapi` Implements a DBAPI (PEP-249) and SQLAlchemy dialect,
that enables SQL access on elasticsearch clusters for query only access.
On Elastic Elasticsearch:
Uses Elastic X-Pack [SQL API](https://www.elastic.co/guide/en/elasticsearch/reference/current/xpack-sql.html)
On AWS ES, opendistro Elasticsearch:
[Open Distro SQL](https://opendistro.github.io/for-elasticsearch-docs/docs/sql/)
This library supports Elasticsearch 7.X versions.
### Installation
```bash
$ pip install elasticsearch-dbapi
```
To install support for AWS Elasticsearch Service / [Open Distro](https://opendistro.github.io/for-elasticsearch/features/SQL%20Support.html):
```bash
$ pip install elasticsearch-dbapi[opendistro]
```
### Usage:
#### Using DBAPI:
```python
from es.elastic.api import connect
conn = connect(host='localhost')
curs = conn.cursor()
curs.execute(
"select * from flights LIMIT 10"
)
print([row for row in curs])
```
#### Using SQLAlchemy execute:
```python
from sqlalchemy.engine import create_engine
engine = create_engine("elasticsearch+http://localhost:9200/")
rows = engine.connect().execute(
"select * from flights LIMIT 10"
)
print([row for row in rows])
```
#### Using SQLAlchemy:
```python
from sqlalchemy import func, select
from sqlalchemy.engine import create_engine
from sqlalchemy.schema import MetaData, Table
engine = create_engine("elasticsearch+http://localhost:9200/")
logs = Table("flights", MetaData(bind=engine), autoload=True)
count = select([func.count("*")], from_obj=logs).scalar()
print(f"COUNT: {count}")
```
#### Using SQLAlchemy reflection:
```python
from sqlalchemy.engine import create_engine
from sqlalchemy.schema import Table, MetaData
engine = create_engine("elasticsearch+http://localhost:9200/")
logs = Table("flights", MetaData(bind=engine), autoload=True)
print(engine.table_names())
metadata = MetaData()
metadata.reflect(bind=engine)
print([table for table in metadata.sorted_tables])
print(logs.columns)
```
#### Connection Parameters:
[elasticsearch-py](https://elasticsearch-py.readthedocs.io/en/master/index.html)
is used to establish connections and transport, this is the official
elastic python library. `Elasticsearch` constructor accepts multiple optional parameters
that can be used to properly configure your connection on aspects like security, performance
and high availability. These optional parameters can be set at the connection string, for
example:
```bash
elasticsearch+http://localhost:9200/?http_compress=True&timeout=100
```
will set transport to use gzip (http_compress) and timeout to 10 seconds.
For more information on configuration options, look at `elasticsearch-py`’s documentation:
- [Transport Options](https://elasticsearch-py.readthedocs.io/en/master/connection.html#transport)
- [HTTP tranport](https://elasticsearch-py.readthedocs.io/en/master/transports.html#urllib3httpconnection)
The connection string follows RFC-1738, to support multiple nodes you should use `sniff_*` parameters
#### Fetch size
By default the maximum number of rows which get fetched by a single query
is limited to 10000. This can be adapted through the `fetch_size`
parameter:
```python
from es.elastic.api import connect
conn = connect(host="localhost", fetch_size=1000)
curs = conn.cursor()
```
If more than 10000 rows should get fetched then
[max_result_window](https://www.elastic.co/guide/en/elasticsearch/reference/7.x/index-modules.html#dynamic-index-settings)
has to be adapted as well.
#### Time zone
By default, elasticsearch query time zone defaults to `Z` (UTC). This can be adapted through the `time_zone`
parameter:
```python
from es.elastic.api import connect
conn = connect(host="localhost", time_zone="Asia/Shanghai")
curs = conn.cursor()
```
### Tests
To run unittest launch elasticsearch and kibana (kibana is really not required but is a nice to have)
```bash
$ docker-compose up -d
$ nosetests -v
```
### Special case for sql opendistro endpoint (AWS ES)
AWS ES exposes the opendistro SQL plugin, and it follows a different SQL dialect.
Using the `odelasticsearch` driver:
```python
from sqlalchemy.engine import create_engine
engine = create_engine(
"odelasticsearch+https://search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/"
)
rows = engine.connect().execute(
"select count(*), Carrier from flights GROUP BY Carrier"
)
print([row for row in rows])
```
Or using DBAPI:
```python
from es.opendistro.api import connect
conn = connect(host='localhost',port=9200,path="", scheme="http")
curs = conn.cursor().execute(
"select * from flights LIMIT 10"
)
print([row for row in curs])
```
### Opendistro (AWS ES) Basic authentication
Basic authentication is configured as expected on the <username>,<password> fields of the URI
```python
from sqlalchemy.engine import create_engine
engine = create_engine(
"odelasticsearch+https://my_user:my_password@search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/"
)
```
IAM AWS Authentication keys are passed on the URI basic auth location, and by setting `aws_keys`
Query string keys are:
- aws_keys
- aws_region
```python
from sqlalchemy.engine import create_engine
engine = create_engine(
"odelasticsearch+https://<AWS_ACCESS_KEY>:<AWS_SECRET_KEY>@search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/?aws_keys=1&&aws_region=<AWS_REGION>"
)
```
IAM AWS profile is configured has a query parameter name `aws_profile` on the URI. The value for the key provides the AWS region
```python
from sqlalchemy.engine import create_engine
engine = create_engine(
"odelasticsearch+https://search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/?aws_profile=us-west-2"
)
```
Using the new SQL engine:
Opendistro 1.13.0 brings (enabled by default) a new SQL engine, with lots of improvements and fixes.
Take a look at the [release notes](https://github.com/opendistro-for-elasticsearch/sql/blob/develop/docs/dev/NewSQLEngine.md)
This DBAPI has to behave slightly different for SQL v1 and SQL v2, by default we comply with v1,
to enable v2 support, pass `v2=true` has a query parameter.
```
odelasticsearch+https://search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/?aws_profile=us-west-2&v2=true
```
To connect to the provided Opendistro ES on `docker-compose` use the following URI:
`odelasticsearch+https://admin:admin@localhost:9400/?verify_certs=False`
### Known limitations
This library does not yet support the following features:
- Array type columns are not supported. Elaticsearch SQL does not support them either.
SQLAlchemy `get_columns` will exclude them.
- `object` and `nested` column types are not well supported and are converted to strings
- Indexes that whose name start with `.`
- GEO points are not currently well-supported and are converted to strings
- AWS ES (opendistro elascticsearch) is supported (still beta), known limitations are:
* You are only able to `GROUP BY` keyword fields (new [experimental](https://github.com/opendistro-for-elasticsearch/sql#experimental)
opendistro SQL already supports it)
* Indices with dots are not supported (indices like 'audit_log.2021.01.20'),
on these cases we recommend the use of aliases
نیازمندی
| مقدار | نام |
|---|---|
| <7.14,>7 | elasticsearch |
| <22.0,>=21.0 | packaging |
| - | sqlalchemy |
| - | requests-aws4auth |
| - | boto3 |
نحوه نصب
نصب پکیج whl elasticsearch-dbapi-0.2.9:
pip install elasticsearch-dbapi-0.2.9.whl
نصب پکیج tar.gz elasticsearch-dbapi-0.2.9:
pip install elasticsearch-dbapi-0.2.9.tar.gz