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Articles by Apache Arrow
Aggregating Millions of Groups Fast in Apache Arrow DataFusion
Skip to content By Andrew Lamb Raphael Taylor-Davies Daniël Heres / Aug 01, 2023 / Developer, Apache Arrow TLDR Grouped aggregations are a core part of any analytic tool, creating understandable summaries of huge data volumes. Apache Arrow DataFusion’s parallel aggregation capability is 2-3x faster in version 28.0.0 for queries with a large number (10,000 or more) of groups. Improving aggregation performance matters to us as users of DataFusion.
MongoDB Launches Four New Capabilities for Developers to Reduce the Operational Overhead of Building Applications
News | Feeds | Email MongoDB Launches Four New Capabilities for Developers to Reduce the Operational Overhead of Building Applications Saturday, June 24, 2023 MongoDB Atlas expands programming language support to simplify deploying resources on AWS using infrastructure-as-code New Kotlin Driver for MongoDB enables developers to build server-side applications on MongoDB with the Kotlin programming language MongoDB Atlas Kubernetes Operator now simplifies working with containerized applications...
Introduction to Apache Arrow
Skip to content By Anais Dotis-Georgiou / Jan 09, 2023 / InfluxDB, InfluxDB IOx, Apache Arrow A look at what Apache Arrow is, how it works, and some of the companies using it as a critical component in their architecture. Over the past few decades, leveraging big datasets required businesses to perform increasingly complex analysis. Advancements in query performance, analytics, and data storage are largely a result of greater access to memory.
A gentle introduction to Apache Arrow with Apache Spark and Pandas
This time I am going to try to explain how can we use Apache Arrow in conjunction with Apache Spark and Python. First, let me share some basic concepts about this open source project. [Apache Arrow] Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware.
Feather: A Fast On-Disk Format for Data Frames for R and Python, powered by Apache Arrow
This past January, we (Hadley and Wes) met and discussed some of the systems challenges facing the Python and R open source communities. In particular, we wanted to see if there were some opportunities to collaborate on tools for improving interoperability between Python, R, and external compute and storage systems.
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