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Python Connector Libraries for Apache Impala Data Connectivity. Integrate Apache Impala with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

Use Dash to Build to Web Apps on Impala Data



Create Python applications that use pandas and Dash to build Impala-connected web apps.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Impala, the pandas module, and the Dash framework, you can build Impala-connected web applications for Impala data. This article shows how to connect to Impala with the CData Connector and use pandas and Dash to build a simple web app for visualizing Impala data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Impala data in Python. When you issue complex SQL queries from Impala, the driver pushes supported SQL operations, like filters and aggregations, directly to Impala and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Impala Data

Connecting to Impala data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

In order to connect to Apache Impala, set the Server, Port, and ProtocolVersion. You may optionally specify a default Database. To connect using alternative methods, such as NOSASL, LDAP, or Kerberos, refer to the online Help documentation.

After installing the CData Impala Connector, follow the procedure below to install the other required modules and start accessing Impala through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize Impala Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.apacheimpala as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Impala Connector to create a connection for working with Impala data.

cnxn = mod.connect("Server=127.0.0.1;Port=21050;")

Execute SQL to Impala

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT City, CompanyName FROM Customers WHERE Country = 'US'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-apacheimpalaedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Impala data and configure the app layout.

trace = go.Bar(x=df.City, y=df.CompanyName, name='City')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Impala Customers Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Impala data.

python apacheimpala-dash.py

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Download a free, 30-day trial of the CData Python Connector for Impala to start building Python apps with connectivity to Impala data. Reach out to our Support Team if you have any questions.



Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.apacheimpala as mod
import plotly.graph_objs as go

cnxn = mod.connect("Server=127.0.0.1;Port=21050;")

df = pd.read_sql("SELECT City, CompanyName FROM Customers WHERE Country = 'US'", cnxn)
app_name = 'dash-apacheimpaladataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.City, y=df.CompanyName, name='City')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Impala Customers Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)