Let us understand how we can load data from HDFS location into Spark Metastore table. Let us start the spark context for this Notebook so that we can execute the code provided.
Key Concepts Explanation
Using Spark SQL, Scala, and Pyspark CLIs
We can use the load command without LOCAL to get data from an HDFS location into a Spark Metastore Table. The user running the load command from the HDFS location needs to have write permissions on the source location as data will be moved. Make sure the user has write permissions on the source location.
Data Loading Process
- First, copy the data into the HDFS location where the user has write permissions.
- Truncate the table and then load the data from the HDFS location into the Hive table.
Hands-On Tasks
- Truncate the table and load the data from the HDFS location into the Hive table.
- Use Spark SQL with Python or Scala to perform truncation, data loading, and data retrieval operations.
Conclusion
In this article, we explored how to load data from an HDFS location into a Spark Metastore table. By following the provided steps and utilizing Spark SQL, Scala, or Pyspark CLIs, you can efficiently manage data in your environment. Practice these concepts to enhance your skills and don’t hesitate to engage with the community for further learning.
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