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10-23-2024 01:35 AM
1. Access the S3 bucket directly using AWS credentials
spark = SparkSession.builder \
.appName("S3Access") \
.config("spark.hadoop.fs.s3a.access.key", "<your-access-key-id>") \
.config("spark.hadoop.fs.s3a.secret.key", "<your-secret-access-key>") \
.getOrCreate()
2. Databricks encourages the use of the SparkSession object, which provides a unified entry point for working with Spark.
from pyspark.sql import SparkSession
# Create a SparkSession
spark = SparkSession.builder.appName("ServerlessComputeExample").getOrCreate()
3. Serverless compute automatically scales resources based on workload demands. This can be beneficial for Delta tables as it ensures that sufficient resources are available for large-scale data processing tasks.
