--- title: Polars in Aggregate: Streaming Expands, Lakehouse I/O,... description: A quarterly recap of Polars development covers 12 releases, 778 merged PRs, and 95 contributors since December. Highlights include the streaming engine gaining... canonical: https://daily.dev/posts/polars-in-aggregate-streaming-expands-lakehouse-i-o-and-cloud-profiling-nyhjplt7k twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Polars in Aggregate: Streaming Expands, Lakehouse I/O, and Cloud Profiling | daily.dev og:description: A quarterly recap of Polars development covers 12 releases, 778 merged PRs, and 95 contributors since December. Highlights include the streaming engine gaining... og:url: https://daily.dev/posts/polars-in-aggregate-streaming-expands-lakehouse-i-o-and-cloud-profiling-nyhjplt7k og:image: https://api.daily.dev/og/posts/nYhjPLT7k.png og:image:alt: Polars in Aggregate: Streaming Expands, Lakehouse I/O, and Cloud Profiling og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Polars in Aggregate: Streaming Expands, Lakehouse I/O, and Cloud Profiling **[Polars Blog](https://daily.dev/sources/polars)** · 4 min read · 0 upvotes · 0 comments ## Summary A quarterly recap of Polars development covers 12 releases, 778 merged PRs, and 95 contributors since December. Highlights include the streaming engine gaining merge and AsOf joins, streaming scan/sink support across all major formats (CSV, NDJSON, IPC), direct cloud streaming for scan_ndjson and scan_lines, new sink_delta() and refactored scan_delta() with predicate pushdown, a completed Iceberg read/write roundtrip via sink_iceberg(), a new Query Profiler for Polars Cloud that helped tune a TPC-H query to run 54% faster and 64% cheaper, a 10% faster cost-based distributed query planner, and a new pl.PartitionBy API for consistent output partitioning. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Does Polars support writing back to Apache Iceberg tables now? Yes, Polars 1.39 completes the Iceberg read/write roundtrip by adding sink_iceberg(), letting the streaming engine scan, transform, and commit a new Iceberg snapshot directly. Previously Polars could only read Iceberg tables. scan_iceberg() also now accepts table identifier strings for easier catalog-backed integration. _Track Polars Iceberg support like this on daily.dev before wiring it into a lakehouse pipeline._ ### How do I write a lazy Polars query directly to Delta Lake without materializing it in memory? Use sink_delta(), added in Polars 1.37, which lets lazy queries write directly to Delta Lake without first materializing the full result in memory. Polars 1.38 also refactored scan_delta() onto the Python dataset interface and added file-statistics-based predicate pushdown, making selective batch reads cheaper. _daily.dev helps engineers keep up with Delta Lake and Polars I/O changes like this one._ ### How much can tuning cluster size with the Polars Cloud Query Profiler actually save on a distributed query? Using the Query Profiler to move a TPC-H query from a single oversized machine to a better-fitting cluster across five tuning runs resulted in a query that ran 54% faster and 64% cheaper. The profiler exposes per-stage resource metrics, physical-plan details, shuffle percentages, and node-level CPU, RAM, and network usage. _daily.dev surfaces cost and performance tuning stories like this for teams sizing data clusters._ ## Similar posts on daily.dev - [Release of Polars 2.0](https://daily.dev/posts/release-of-polars-2-0-84cwf427y) · Polars Blog · 1 upvotes · 0 comments - [Announcing Polars 1.44](https://daily.dev/posts/announcing-polars-1-44-nyx9iebfn) · Polars Blog · 1 upvotes · 0 comments - [Decathlon Switches to Polars to Optimize Data Pipelines and Infrastructure Costs](https://daily.dev/posts/decathlon-switches-to-polars-to-optimize-data-pipelines-and-infrastructure-costs-5gcd7b1tn) · InfoQ · 70 upvotes · 0 comments - [Apache Polaris with PyIceberg: A Guide](https://daily.dev/posts/apache-polaris-with-pyiceberg-a-guide-ykkijp45z) · Dremio Blog · 0 upvotes · 0 comments --- Tags: [#python](https://daily.dev/tags/python), [#data-engineering](https://daily.dev/tags/data-engineering), [#apache-iceberg](https://daily.dev/tags/apache-iceberg), [#polars](https://daily.dev/tags/polars) [View this post on daily.dev](https://daily.dev/posts/polars-in-aggregate-streaming-expands-lakehouse-i-o-and-cloud-profiling-nyhjplt7k) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Polars in Aggregate: Streaming Expands, Lakehouse I/O, and Cloud Profiling","url":"https://daily.dev/posts/polars-in-aggregate-streaming-expands-lakehouse-i-o-and-cloud-profiling-nyhjplt7k","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/polars-in-aggregate-streaming-expands-lakehouse-i-o-and-cloud-profiling-nyhjplt7k"},"datePublished":"2026-08-16T08:53:17.380Z","dateModified":"2026-08-16T08:55:34.875Z","description":"A quarterly recap of Polars development covers 12 releases, 778 merged PRs, and 95 contributors since December. 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