Top 3 Things You Can Do to Get Fast Upsert Performance in Apache Hudi™
Blog post from Onehouse
Apache Hudi is gaining traction among developers for its robust capabilities in managing large-scale datasets, particularly through the efficient execution of upserts. The choice between its two storage table types—Copy-On-Write (COW) and Merge-On-Read (MOR)—plays a crucial role in optimizing upsert performance. COW tables are simpler operationally and offer zero read amplification but come with higher write amplification due to synchronous merging. Conversely, MOR tables are more complex but are write-optimized, as they handle updates through log files that are later compacted, reducing write amplification but increasing read complexity. The selection of an indexing strategy is also vital, as Hudi's indexing layer minimizes full-table scans during upserts, with options ranging from global to non-global indexes like Bloom, Simple, and Bucket indexes, each catering to different workload requirements. Partitioning strategy impacts both query and ingestion performance, where overly granular partitions can lead to inefficiencies. The blog emphasizes tailoring configurations and tuning Hudi to specific workload types to maximize upsert efficiency, advising a balance between partition granularity and indexing choices.
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