Extract Data FROM Hadoop Using Python

To extract data from Hadoop using Python, you can use several libraries and methods, depending on your specific requirements and Hadoop ecosystem components (e.g., HDFS, Hive, Pig) you are working with. Here are some common approaches:

1. Using HDFS with Python:

   • You can use the hdfs library in Python to interact with the Hadoop Distributed File System (HDFS).
   • Install the hdfs library if you haven’t already:
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   pip install hdfs
   • Example Python code to list files in HDFS:
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   from hdfs import InsecureClient # Connect to HDFS client = InsecureClient('http://<HDFS_NAMENODE_HOST>:<HDFS_NAMENODE_PORT>', user='<HDFS_USER>') # List files in a directory files = client.list('/path/to/hdfs/directory') for file in files: print(file)

2. Using WebHDFS REST API:

   • You can use the WebHDFS REST API to interact with HDFS from Python using HTTP requests.
   • You can make HTTP requests to HDFS endpoints to perform operations like listing files, reading files, or writing files.

3. Using PyArrow for Parquet Files:

   • If you’re working with Parquet files in Hadoop, you can use the pyarrow library to read and write Parquet files in Python.
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   import pyarrow.parquet as pq # Read a Parquet file from HDFS table = pq.read_table('hdfs://<HDFS_NAMENODE_HOST>:<HDFS_NAMENODE_PORT>/path/to/parquet/file.parquet') # Convert the table to a pandas DataFrame df = table.to_pandas() # Process the DataFrame

4. Using PyHive for Hive:

   • If your data is stored in Hive tables, you can use the pyhive library to connect to Hive from Python and execute SQL queries.
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   from pyhive import hive # Connect to Hive conn = hive.connect(host='<HIVE_SERVER_HOST>', port=<HIVE_SERVER_PORT>, username='<HIVE_USER>') # Execute a Hive query cursor = conn.cursor() cursor.execute('SELECT * FROM your_hive_table') # Fetch the results results = cursor.fetchall() # Process the results

5. Using Other Hadoop Ecosystem Components:

   • Depending on your use case, you may need to interact with other Hadoop ecosystem components like Pig, Spark, or HBase using Python libraries and APIs specific to those components.

Make sure to install the required Python libraries for your chosen method, and replace the placeholders (e.g., <HDFS_NAMENODE_HOST>, <HIVE_SERVER_HOST>) with the actual hostnames and configuration details of your Hadoop cluster.