Format choice shows up as a bill, not a performance complaint. A working breakdown of where the money actually goes across Parquet, JSON and CSV: column pruning, row-group skipping, the gzip splittability trap, and request overhead. Includes a procedure for measuring the difference on your own data, and an honest account of where Parquet costs you.
Managed Iceberg compaction in S3 Tables removes real operational work, but it will not tell you when it stops. A practical look at the maintenance jobs that fail silently, the retention cascade that keeps superseded data on your bill for two weeks, how compaction charges actually accumulate, and the handful of knobs worth touching.
A practical comparison of Parquet, JSON and CSV on cost and query performance, covering how each billing model changes the answer, the mechanics behind columnar savings, the failure modes that cancel them out, and a six-step way to model the migration before you commit to it.
A backfill that exits zero can still be missing a week of data, and nothing will tell you. This is a practical guide to the failure families behind silent gaps: pagination drift under a mutating source, retries that duplicate pages, prefix layouts designed for writes instead of reads, the seam where backfill meets live ingest, and the storage class rules that make mistakes expensive. Includes deterministic key derivation, S3 conditional writes, Athena partition projection, and a per-window manifest pattern that turns completeness into something you can query.