🍪

Essential cookies keep authentication working. With your permission, we also use analytics to improve the product. Privacy Policy

DDataEngPrep.tech
Home
PricingBlog
Sign InStart Free→
Home/Questions/Spark/Big Data/What file format does Delta Lake use, and why is it beneficial?

What file format does Delta Lake use, and why is it beneficial?

Spark/Big Dataeasy0.4 min read

Reviewed by Aditya Kumar · Last reviewed 2026-03-25

**Format**: Parquet for data files + JSON transaction log in _delta_log. **Parquet Benefits**: Columnar; compression (snappy, zstd); predicate pushdown; schema in footer. **Delta Additions**: Transaction log for ACID; versioning; MERGE/UPDATE/DELETE; compaction...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Part of the Apache Spark Interview Preparation Hub
Explore Apache Spark Hub→
Reported in Interview Loops AtClick to view company-specific questions
🏢 Chryselys Interview Hub→
Expert Answer
71 words

Format: Parquet for data files + JSON transaction log in _delta_log.

Parquet Benefits: Columnar; compression (snappy, zstd); predicate pushdown; schema in footer.

Delta Additions: Transaction log for ACID; versioning; MERGE/UPDATE/DELETE; compaction (checkpoint.parquet).

Why Both: Parquet gives storage efficiency; log gives transactional semantics. Best of both.

Scalability Trade-offs: Log grows; checkpoint files aggregate. VACUUM and OPTIMIZE manage.

Cost Implications: Parquet compression ~5–10x. Delta log ~1–5% overhead. Combined = efficient storage + ACID.

⚡
Pro Tip

Pro-Move: 'Zstd compression; 30% smaller than snappy, same read speed.' Red Flag: Deleting checkpoint files—slows log replay.

Related Spark/Big Data Questions

mediumWhat is the difference between repartition and coalesce in Apache Spark?FreehardWhat is the difference between SparkSession and SparkContext in Spark?FreemediumWhat is the difference between cache() and persist() in Spark? When would you use each?FreemediumWhat is the difference between groupByKey and reduceByKey in Spark?FreemediumWhat is the difference between narrow and wide transformations in Apache Spark? Explain with examples.Free

According to DataEngPrep.tech, this is one of the most frequently asked Spark/Big Data interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.

← Back to all questionsMore Spark/Big Data questions →
Topic Hubs
All Topic Hubs (12 Competencies) →All 1,863+ QuestionsSQL Interview QuestionsApache Spark QuestionsPySpark QuestionsPython for Data EngineersSystem Design InterviewData Modeling & WarehousingStreaming (Kafka/Flink)SQL Window FunctionsETL Pipeline Design
Company Hubs
All Company Hubs (100+ Companies) →AmazonGoogleMetaDatabricksSnowflakeNetflixUberStripeMicrosoftAppleGoldman SachsAWS Engineering
Academies & Guides
All Guides & ArticlesData Engineering AcademyForward Deployed AI AcademyClient Simulation StudioApache Airflow QuestionsAzure Data EngineerBehavioral & STAR MethodCloud & Distributed Tools
AI Tools & Products
Answer Analyzer (Free)AI Mock InterviewsSQL PlaygroundATS Resume AnalyzerOffline PDF Answer VaultsMembership & Pricing
Company
About & Editorial PolicyContact UsAI DisclosureDisclaimerTerms of ServicePrivacy Policy
© 2026 DataEngPrep.tech. All rights reserved.
AboutBlogContactDisclaimer