Releasesby Glyphspark-nlp 6.1.5
📢 Spark NLP 6.1.5: Smarter Readers and More Resilient Pipelines Spark NLP 6.1.5 focuses on improving data ingestion reliability and pipeline flexibility. This release enhances reader components with better fault tolerance, broader input support, and introduces a new ReaderAssembler annotator for streamlined integration.
Also shipped Oct 9, 2025John Snow Labs in October 2025 →
[Preview] DuckLake 0.3
As we announced earlier this year, MotherDuck now supports DuckLake , an integrated data lake and catalog format. DuckLake 0.3 makes working with DuckLake more robust, including CHECKPOINT for easy maintenance , new paths for Iceberg interoperability, spatial geometry types , and MERGE INTO support .
Modal 1.2.0
In this release, we're introducing the concept of "App tags", which are simple key-value metadata that can be included to provide additional organizational context.
Workers - You can now deploy full-stack apps on Workers using Terraform
You can now upload Workers with static assets (like HTML, CSS, JavaScript, images) with the Cloudflare Terraform provider v5.11.0 ↗ , making it even easier to deploy and manage full-stack apps with IaC.
Workers - You can now deploy and manage Workflows in Terraform
You can now create and manage Workflows using Terraform, now supported in the Cloudflare Terraform provider v5.11.0 ↗ . Workflows allow you to build durable, multi-step applications -- without needing to worry about retrying failed tasks or managing infrastructure.
Performance improvements
- Sorting is 2x+ faster: Complete rewrite of sorting uses less memory and scales better across threads for ORDER BY, window functions, and list sorting More efficient small writes: Appending small numbers of rows now writes far fewer bytes 5x faster checkpointing: Reuses table metadata when tables aren't altered during checkpoint Parallel connection...
SQL syntax updates
- MERGE INTO statement: Standard SQL upserts without requiring primary keys or indexes FILL() window function: Interpolate missing values in ordered data Python-style macro arguments: Macros accept positional or named arguments for any parameter STRUCT to MAP cast: Direct casting between struct and map types
More from spark-nlpEvery spark-nlp release →
spark-nlp 6.2.0
📢 Spark NLP 6.2.0: A new stage for unstructured document ingestion and processing at scale Spark NLP 6.2.0 introduces key upgrades across entity extraction, document normalization, HTML reading, and GGUF-based models.
spark-nlp 6.2.1
📢 Spark NLP 6.2.1: Enhanced hierarchical document processing and training optimizations Spark NLP 6.2.1 brings significant improvements to document ingestion with expanded hierarchical support, XML processing enhancements, and optimizations for NerDL training.
spark-nlp 6.2.2
📢 Spark NLP 6.2.2: Bugfix Release Spark NLP 6.2.2 brings bug fixes to WordEmbeddings and NerDLApproach logging. 🐛 Bug Fixes - WordEmbeddings: Fixed a bug where WordEmbeddings would duplicate input tokens in the output - NerDLApproach: Fixed a bug during logging, that would show inaccurate training/validation counts.
spark-nlp 6.2.3
📢 Spark NLP 6.2.3: Further Improvements for NerDL Spark NLP 6.2.3 introduces targeted improvements to training performance and stability of NerDLApproach and bug fixes for CamemBertForTokenClassification. NerDLApproach now uses new internal data-loading behavior, and improving training speed and preventing out-of-memory errors.
spark-nlp 6.3.1
📢 Spark NLP 6.3.1: LLM Backend Upgrade and Document Processing Improvements Spark NLP 6.3.1 focuses on strengthening distributed local LLM inference by upgrading the jsl-llamacpp backend to a newer llama.cpp release, while also delivering important improvements in document structure handling and metadata consistency.
spark-nlp 6.3.2
📢 Spark NLP 6.3.2: Scala 2.13 Support, Layout-Aware Images, and Enhanced LightPipeline Tracking Spark NLP 6.3.2 is a foundational release that introduces official support for Scala 2.13, alongside important improvements in document layout understanding and lightweight inference workflows.
spark-nlp 6.3.3
📢 Spark NLP 6.3.3: ModernBERT Embeddings, Vector DB Integration, and Layout-Aware Document Processing Spark NLP 6.3.3 is a feature-packed release aimed at practitioners building modern NLP and multimodal document pipelines.
spark-nlp 6.4.0
📢 Spark NLP 6.4.0: LLM-Powered Entity Extraction, Expanded Document Readers, and Pipeline Robustness Spark NLP 6.4.0 is a feature-rich release focused on bringing LLM-powered extraction into standard NLP pipelines, dramatically expanding the document reader ecosystem, and hardening production ingestion workflows.