Python HDFS

To interact with Hadoop Distributed File System (HDFS) using Python, you can use the hdfs library, which provides a Pythonic interface for performing various HDFS operations. Here’s how you can use Python to work with HDFS:

1. Install the hdfs Library: You need to install the hdfs library first. You can install it using pip:

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   pip install hdfs

2. Import the Client Class: In your Python script, you can import the Client class from the hdfs library to create a client object for interacting with HDFS.

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   from hdfs import InsecureClient

3. Create an HDFS Client: You’ll need to create an HDFS client object by specifying the HDFS server’s URL and port. If you are using a secured cluster, you may need to configure additional options for authentication.

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   hdfs_client = InsecureClient('http://<HDFS_SERVER>:<HDFS_PORT>', user='<HDFS_USER>')

4. Perform HDFS Operations: You can now use the HDFS client object to perform various operations, such as listing files and directories, uploading files, downloading files, creating directories, and more.

   Here are some examples of common HDFS operations using the hdfs library:

   • List Files and Directories:

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     contents = hdfs_client.list('/path/to/directory') print(contents)

   • Upload a File to HDFS:

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     local_file = '/path/to/local/file.txt' hdfs_path = '/path/in/hdfs/file.txt' hdfs_client.upload(hdfs_path, local_file)

   • Download a File from HDFS:

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     hdfs_path = '/path/in/hdfs/file.txt' local_file = '/path/to/local/file.txt' hdfs_client.download(hdfs_path, local_file)

   • Create a Directory:

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     hdfs_path = '/path/in/hdfs/new_directory' hdfs_client.makedirs(hdfs_path)

5. Close the HDFS Client: Once you’re done with the HDFS client, it’s a good practice to close it.

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   hdfs_client.close()