Delta Lake interview questionsQuestion 1 of 2
Delta Lake interview question · Question 1 of 2
What problems does Delta Lake solve?
Short answer
Plain files in a data lake have no transactions, so failed or concurrent writes can leave partial data, readers can see inconsistent states, and there is no schema enforcement or easy way to update rows. Delta Lake adds a transaction log on top of Parquet files that provides atomic commits, consistent snapshot reads, schema enforcement with controlled evolution, time travel to earlier versions, and operations such as MERGE, UPDATE and DELETE.
Detailed explanation
| Problem with plain files | Delta Lake answer |
|---|---|
| A failed job leaves half-written output | Atomic commits: files become visible only when the commit is recorded |
| Readers see partial writes | Snapshot isolation from the log |
| Schema drift corrupts tables | Schema enforcement; explicit evolution |
| Updating or deleting rows requires rewriting by hand | MERGE, UPDATE, DELETE |
| No history | Time travel by version or timestamp |
| Listing millions of files is slow | Metadata in the log and checkpoints |
How it works in one sentence
Each write adds a commit file to _delta_log listing added and removed data files; the current table is the result of replaying the log, so a write is either fully in the table or not at all.
Common mistakes
- Saying Delta Lake is a database or a storage service (it is a table format over files).
- Forgetting maintenance: compaction and
VACUUM.
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