How to perform ACID transaction in delta lake

 Delta Lake, an open-source storage layer that brings ACID transactions to Apache Spark and big data workloads, allows you to perform ACID transactions on your data. ACID stands for Atomicity, Consistency, Isolation, and Durability – key properties that ensure the reliability of transactions.

Here's a basic guide on how to perform ACID transactions in Delta Lake:

1. Initialize Delta Lake:

• Make sure you have Delta Lake installed and configured in your Spark environment. You can add the Delta Lake library to your Spark application.

spark.conf.set("spark.jars.packages", "io.delta:delta-core_2.12:1.0.0")

Create a Delta Table:

• Create a Delta table or convert an existing Parquet table into a Delta table. This is done using the DeltaTable API.

import io.delta.tables._ val deltaTable = DeltaTable.forPath("path/to/delta/table")

Start a Transaction:

• Use the as method on the Delta table to start a transaction.

deltaTable.as("myTable").merge(...)

Perform ACID Operations:

• Within the transaction, perform the ACID operations. For example, you can use the merge operation to perform an upsert (update or insert) operation.

deltaTable.as("myTable") .merge(...) .whenMatched.updateAll() .whenNotMatched.insertAll() .execute()

Commit the Transaction:

• Use the execute method to commit the transaction.

deltaTable.as("myTable").merge(...).execute()

Rollback (Optional):

• If needed, you can use Spark's built-in transaction management to rollback a transaction in case of an error. Delta Lake leverages Spark's native support for transactions.

spark.sql("ROLLBACK")

Remember, Delta Lake provides additional features like schema evolution, time travel, and data versioning, making it a powerful choice for managing big data workloads with ACID properties. Ensure you refer to the Delta Lake documentation for the version you are using for detailed and up-to-date information.