Let’s understand what are Delta Lake compact and checkpoint and why they are important.
Checkpoint
There are two known checkpoints mechanism in Apache Spark that can confuse us with DeltaLake checkpoint, so let’s understand them and how they differ from each other:
Spark RDD Checkpoint
Checkpoint in Spark RDD is a mechanism to persist current RDD to a file in a dedicated checkpoint directory while all references to its parent RDDs are removed.
This operation, by default, breaks data lineage when used without auditing.
In the previous part, you learned what ACID transactions are. In this part, you will understand how Delta Transaction Log, named DeltaLog, is achieving ACID.
Transaction Log
A transaction log is a history of actions executed by a (TaDa 💡) database management system with the goal to guarantee ACID properties over a crash.
DeltaLake transaction log - DetlaLog
DeltaLog is a transaction log directory that holds an ordered record of every transaction committed on a Delta Lake table since it was created.
The goal of DeltaLog is to be the single source of truth for readers who read from the same table at the same time. That means, parallel readers read the exact same data.
This is achieved by tracking all the changes that users do: read, delete, update, etc. in the DeltaLog.
