●Change8

Migrating to Ray ray-2.54.0

Version ray-2.54.0 introduces 2 breaking changes. This guide details how to update your code.

Released: 2/18/2026

2
Breaking Changes
2
Migration Steps
18
Affected Symbols

⚠️ Check Your Code

If you use any of these symbols, you need to read this guide:

read_sqlUDFExprwrite_parquetDefaultClusterAutoscalerV2UnionOperatorActorPoolMapOperatorAutoscalingCoordinatorDefaultAutoscalerV2StreamingRepartitionTensorArrayStatsActorray.dataSortTENSOR_COLUMN_NAMEStatefulShuffleAggregation.finalizeOutputSplitterserve.batchQueueMonitor

Breaking Changes

●Issue #1

Removed top-level `ray.data` imports to decouple Ray Train from Ray Data. Users must now import necessary components directly from `ray.data` submodules or use the new extension type locations.

●Issue #2

Removed deprecated constant `TENSOR_COLUMN_NAME`. Users relying on this constant must update their code.

Migration Steps

  1. 1
    If you were using top-level imports from `ray.data`, update them to import from specific submodules or use the new locations for extension types.
  2. 2
    If you were using the deprecated constant `TENSOR_COLUMN_NAME`, replace it with the appropriate alternative.

Release Summary

This release introduces significant new features in Ray Data, including checkpointing, expanded Compute Expressions, and Databricks UC credential support, alongside major enhancements to cluster autoscaling and performance optimizations. Ray Serve gains queue-based autoscaling for TaskConsumers and improved deployment observability.

Need More Details?

View the full release notes and all changes for Ray ray-2.54.0.

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