Lars Kroll
Software Engineer at databricks
Amsterdam, North Holland, Netherlands
Summary
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RockstarLars Kroll is a software engineer with five years’ experience, currently working at Databricks in Amsterdam and contributing to high-impact open-source projects. He focuses on backend development and test automation, notably improving performance and correctness of the RoaringBitmap library used by Apache Spark, Netflix Atlas and others. Lars has also contributed to Delta Lake, performing refactors and test improvements that enhance stability in large-scale data storage workflows. He brings a pragmatic emphasis on performance-sensitive iterator logic and API design, paired with disciplined code-quality work. Colleagues can expect a developer who balances low-level algorithmic fixes with pragmatic engineering hygiene in distributed data systems.
5 years of coding experience
Github Skills (21)
algorithm10
algorithms10
bitmap10
spark10
delta-lake10
testing10
big-data10
roarr10
data-structure10
bitset10
java10
scala10
javas10
data-structures10
bitmaps10
Programming languages (2)
Github contributions (5)
delta-io/delta
Mar 2021 - Jan 2023
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Role in this project:
Back-end Developer
Back-end DeveloperContributions:168 reviews, 31 commits, 24 PRs in 1 year 9 months
Contributions summary:Lars Kroll primarily focused on refactoring and improving the codebase related to the Delta Lake storage framework. His contributions involved minor refactors, code cleanup, and style improvements across multiple files. Additionally, he was involved in creating helper methods for executing merges and refactoring existing tests. The changes indicate a focus on maintaining code quality, enhancing the existing features, and improving the overall stability of the project.
analyticsprestodbflinkbig-dataspark
RoaringBitmap/RoaringBitmap
May 2021 - Dec 2022
A better compressed bitset in Java: used by Apache Spark, Netflix Atlas, Apache Pinot, Tablesaw, and many others
Role in this project:Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:19 reviews, 6 commits, 7 PRs in 1 year 7 months
Contributions summary:Lars primarily focused on improving the performance and correctness of the `roaringbitmap` library's iterators, particularly for the `Roaring64Bitmap` implementation. Their work included implementing a faster `advanceIfNeeded` method, fixing bugs related to iterating into gaps within the data, and adding new testing methods. The user also contributed new APIs for relative range consumption and for iterating over data within a range. These changes involved modifications to the core data structures and iterator logic, along with extensive testing.
bigdataroaring-bitmapsspark-mlroaringbitmapdruid
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