Managing Data Files in Apache Iceberg

Everything was going great, your data was in your data lake, queries were fast and the SREs were happy. But then things started to slow down. Queries took longer, even specific queries which used to be fast now take a long time. The culprit? Small and unorganized files. The solution? Apache Iceberg’s RewriteDatafile action. In this talk, Russell Spitzer will dive into how RewriteDataFiles can 1) right-size your files, merging small files and splitting large ones, ensuring that no time is waisted in query planning or in opening files; and 2) reorganize the data within your files, supporting hierarchal sort and multidimensional ordering algorithms, enabling you to make sure your data is optimally set out for your queries. With these two capabilities, any table can be kept at peak performance regardless of ingestion patterns and table size. Download PDF

Topics Covered

Apache Iceberg
Table Formats


Russell Spitzer

Russell Spitzer

Russell Spitzer received his Ph.D from UCSF in 2013 after performing a lot of comparisons of protein binding sites. Following that, he became deeply invested in distributed computing and involved in several Apache projects. While working at DataStax, he became a key contributor to the DataStax Spark-Cassandra Connector, and he also worked on both of those (and other) Apache projects. More recently, he has been involved with the Apache Iceberg project and has devoted most of his time to data file management and advancing the table format. Currently, Russell is a PMC member of the Apache Iceberg project.

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