How to Visualize HDFS Data in Python with pandas

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for HDFS, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build HDFS-connected Python applications and scripts for visualizing HDFS data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to HDFS data, execute queries, and visualize the results.

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

Connecting to HDFS Data

Connecting to HDFS 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 authenticate, set the following connection properties:

• Host: Set this value to the host of your HDFS installation.
• Port: Set this value to the port of your HDFS installation. Default port: 50070

Follow the procedure below to install the required modules and start accessing HDFS through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize HDFS Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with HDFS data.

engine = create_engine("hdfs:///?Host=sandbox-hdp.hortonworks.com&Port=50070&Path=/user/root&User=root")

Execute SQL to HDFS

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

df = pandas.read_sql("SELECT FileId, ChildrenNum FROM Files WHERE FileId = '119116'", engine)

Visualize HDFS Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the HDFS data. The show method displays the chart in a new window.

df.plot(kind="bar", x="FileId", y="ChildrenNum")
plt.show()

Free Trial & More Information

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

Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("hdfs:///?Host=sandbox-hdp.hortonworks.com&Port=50070&Path=/user/root&User=root")
df = pandas.read_sql("SELECT FileId, ChildrenNum FROM Files WHERE FileId = '119116'", engine)

df.plot(kind="bar", x="FileId", y="ChildrenNum")
plt.show()