Welcome to the Eventual blog
Join us as we explore innovative ways to handle multimodal datasets, optimize performance, and simplify your data workflows.
Image Embeddings: Tutorial & Examples
Learn about the concept of image embeddings, their various use cases, and best practices for handling them in data processing workflows.
Multimodal Embeddings: Tutorial & Examples
Learn multimodal embedding techniques for cross-modal search, recommendation systems, and content moderation applications.
Daft v0.7.9: Temporal Arithmetic, Video Frame Decoding, and Native UUID
Migrating ETL workloads from Spark means hitting gaps in date arithmetic — functions like `date_add`, `date_diff`, and epoch conversions that Spark users take for granted. Daft v0.7.9 closes that gap
Daft v0.7.5: A Plugin System, 5x Faster Parquet, and a Real-Time Query Debugger
Native Extensions via Stable C ABI, Live Query Dashboard, and 2-5x faster Parquet Reads on Nested Types
How We're Making Observability Better in Daft
Daft Observability Roadmap: metrics, OTEL integration, real-time dashboards, and DataFrame APIs for debugging and monitoring distributed pipelines.
Daft v0.7.4: Arrow-rs, OpenDAL, Flight Shuffle, and Better Metrics
Daft v0.7.4 completes its arrow-rs migration, adds Apache OpenDAL storage support, Flight shuffle for Flotilla, and a full observability stack.
Daft v0.7.3: OTEL for Flotilla, Nightly Builds, and Lance NN Search
Daft v0.7.3 adds distributed observability with df.metrics via OTEL, nightly builds, and native Lance vector search.
Introducing daft.File: Work with Any File, Anywhere
daft.File brings lazy, distributed handling for audio, video, PDFs, and code to Daft DataFrames. One interface, local or remote.
Tuning Daft's Distributed UDFs: Lessons from ByteDance
Learn from the ByteDance Volcengine LAS Team on how to optimize Daft UDFs on Ray. Discover the formula to evenly distribute data across actors.