-
Read the Flat File from Azure Blob Storage:
-
Convert DataFrame to Bytes Format:
- Once you have the DataFrame, you can convert it to bytes format. PySpark DataFrames are already represented in a binary format internally, so you donโt need to explicitly convert them to bytes.
- If you need to extract the raw bytes from the DataFrame, you can use the
collect()
method to retrieve the data as a list of rows, where each row is a tuple of values. Then, you can serialize the rows to bytes using any serialization method (e.g., JSON, Avro, Parquet).
-
Parsing the Data:
- Now that you have the data in bytes format, you can parse it according to your requirements.
- For example, if your flat file is in CSV format, you can parse it using PySparkโs built-in CSV reader or custom logic.
Hereโs a simplified example of reading a CSV file from Azure Blob storage and converting it to bytes format:
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("AzureBlobReader").getOrCreate()
flat_file_df = spark.read.csv("abfss://<container-name>@<storage-account-name>.dfs.core.windows.net/mydata")
json_bytes = flat_file_df.toJSON().collect()[0].encode("utf-8")
Remember to replace <container-name>
and <storage-account-name>
with your actual container and storage account names. Adjust the code according to your specific file format and requirements.
Feel free to adapt this example to your use case, and let me know if you need further assistance! ๐