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AI / Apache Paimon Interview questions

What is Apache Paimon?

Apache Paimon is an open-source lake format for building a real-time Lakehouse architecture that supports both streaming and batch operations. It innovatively combines a data lake format with a Log-Structured Merge-tree (LSM), which lets it bring real-time streaming updates into lake storage instead of treating the lake as append-only.

It grew out of the Flink community as FLIP-188 ("Introduce Built-in Dynamic Table Storage") and was originally shipped as Flink Table Store before becoming an independent Apache project. Paimon graduated from the Apache Incubator to a Top-Level Project in April 2024, and today it integrates deeply with both Apache Flink and Apache Spark, plus read support from Hive, Trino, StarRocks, and Doris.

Its core capabilities are real-time updates via primary key tables, huge append-data processing via append tables, and standard data lake features like ACID transactions, time travel, and schema evolution.

Apache Paimon is best described as:
Before becoming an independent Apache project, Paimon was known as:

More Related questions...

What is Apache Paimon? What is the purpose of Paimon's Catalog abstraction? What are the four types of metastores Paimon catalogs support? Define a primary key table in Paimon? What are the two main table types in Paimon? Describe a Paimon Snapshot? What are Manifest files used for in Paimon? What is a Bucket in Paimon? List the merge engines Paimon supports for primary key tables? What is the default merge engine in Paimon? What is the purpose of the changelog-producer table property? How do you use the sequence.field option in Paimon? What is Paimon's LSM tree used for? What are Sorted Runs in a Paimon LSM tree? Describe what Paimon's system tables are for? How do you use the $snapshots system table? What is the purpose of Tags in Paimon? What is an Append Table in Paimon? How do you apply schema evolution during CDC ingestion into Paimon? What are the consistency guarantees Paimon provides for writers? What is the purpose of the Audit Log system table? Describe the Read-optimized (ro) system table? Why does Paimon combine a lake format with an LSM-tree structure? How does the Deduplicate merge engine handle a DELETE record? What is the difference between the Partial Update and Aggregation merge engines? What is the difference between Fixed Bucket and Dynamic Bucket modes? When should you choose Postpone Bucket mode? What happens when Paimon's sorted runs contain overlapping primary key ranges? Why should changelog-producer be enabled only when necessary? What is the difference between the input and lookup changelog producers? How does the full-compaction changelog producer differ from lookup? Why do concurrent writers to the same partition only get snapshot isolation instead of full isolation? When should you choose the Hive catalog over the filesystem catalog? How can you optimize primary key lookups using the bucket-key option? What is the difference between the sequence.field and rowkind.field options? Explain the execution flow of a two-phase commit when a Paimon writer flushes data? Why is Cross Partitions Upsert more expensive than a normal bucketed upsert? How do you troubleshoot excessive small files from streaming writes into a Paimon table? What is the difference between the audit_log and binlog system tables? Explain the internal working of automatic tag creation with a watermark? When should you choose the REST catalog over the Hive catalog? What happens when you roll back a Paimon table to an earlier tag? How does Paimon achieve streaming-batch unification on the same table? Why does Paimon recommend keeping bucket data size between 200MB and 1GB? What is the difference between the First Row and Deduplicate merge engines? How can you optimize query performance using the read-optimized system table? What is the difference between Paimon's and Apache Iceberg's core design philosophy? Why did Apache Paimon originally start as part of the Flink project, and what is it called now? Which is better and why: lookup or full-compaction changelog producer for a 30-minute-latency pipeline? How do you troubleshoot duplicate rows appearing when using Dynamic Bucket mode with multiple concurrent write jobs?
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