databricks-spark-structured-streaming
This skill provides patterns and best practices for building production Spark Structured Streaming pipelines on Databricks.
Identity proven by GitHub's verified organisation badge (databricks)
- Agents
- Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode
- License
- LicenseRef-Databricks (restricted)
- Pin
- e3df77bpinned Oct 9, 2026
- Context cost
- about 810 tokenswhen the skill loads
- GitHub stars
- 345on databricks/databricks-agent-skills
- Scripts
- None found
What it does
“Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.”
Generated summary from the skill's own text
This skill provides patterns and best practices for building production Spark Structured Streaming pipelines on Databricks. It covers Kafka ingestion, Real-Time Mode, stream joins, stateful operations, checkpoints, and multi-sink writes with detailed reference guides and configuration options.
When to use it
- Building Kafka to Delta or Kafka to Kafka streaming pipelines
- Implementing stateful operations with watermarks and state stores
- Configuring stream-stream or stream-static joins for real-time processing
- Optimizing checkpoint management and trigger selection for cost and performance
When not to
- When batch processing is sufficient for your latency requirements
- Without access to Databricks CLI version 1.0.0 or higher
Install
Restricted license: install from the publisher's repository and read its terms.
These commands install from the publisher's repository and need no account.
skills CLI
npx skills add databricks/databricks-agent-skills --skill databricks-spark-structured-streamingInstalls from the repository's default branch, which may have changed since the commit we checked.
GitHub CLI 2.90 or later
gh skill install databricks/databricks-agent-skills databricks-spark-structured-streaming@e3df77b3f0eb5d70392eb35c6761ca0f2929a4f6Installs the commit we checked (e3df77b).
Copy by hand
Download the folder at e3df77b and put it in .claude/skills/databricks-spark-structured-streaming for Claude Code and in .agents/skills/databricks-spark-structured-streaming for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.
Claude Code plugin
/plugin install databricks@claude-plugins-officialThe publisher's plugin in Claude's official marketplace. It may hold more than this skill, and we have not pinned it.
Copy for your agent
A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.
Prompt
Install the agent skill "databricks-spark-structured-streaming" by Databricks. Source, pinned to commit e3df77b3f0eb5d70392eb35c6761ca0f2929a4f6: https://github.com/databricks/databricks-agent-skills/tree/e3df77b3f0eb5d70392eb35c6761ca0f2929a4f6/plugins/databricks/claude/skills/databricks-spark-structured-streaming 1. Download that folder at exactly this commit. Do not use the default branch. 2. Copy every file unchanged, keeping the folder structure, into .claude/skills/databricks-spark-structured-streaming/ for Claude Code and .agents/skills/databricks-spark-structured-streaming/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist. 3. Do not edit the files, and do not run any script in the folder unless I ask you to. 4. When you are done, list the files you copied and where you put them. Its license is restricted or not stated. Show me the license terms from the repository before you copy anything. Listing and checks: https://www.agentnative.dev/skills/databricks/databricks-spark-structured-streaming
SKILL.md at the pin
The license of this skill does not let us show its files here.
Files
- SKILL.md3.8 KB · 0bef93492116
- agents/
- openai.yaml414 B · 17065383f3c5
- assets/
- databricks.png15 KB · 06873c31ebda
- databricks.svg582 B · 00e528e4d5e6
- references/
- checkpoint-best-practices.md8.6 KB · 8b5df6abe491
- kafka-streaming.md16 KB · 2628e1db4d82
- lakebase-sink-python.md21 KB · de8da28dbb04
- merge-operations.md11 KB · a76cddcad4b0
- multi-sink-writes.md13 KB · 94f252e6d50a
- real-time-mode.md19 KB · 2d43eac45e9b
- stateful-operations.md12 KB · 4655771e9d92
- stream-static-joins.md14 KB · 36c52c108221
- stream-stream-joins.md17 KB · 6bd0bb8a8f35
- streaming-best-practices.md9.6 KB · 82b3fc53304b
- trigger-and-cost-optimization.md14 KB · b4915af8ef80
15 files, 176 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.
Skill folder on GitHub at e3df77bAlso in
The same SKILL.md content appears in these places too. We list it once and credit the oldest public source.
- databricks/databricks-agent-skills/plugins/databricks/codex/skills/databricks-spark-structured-streaming
- databricks/databricks-agent-skills/plugins/databricks/copilot/skills/databricks-spark-structured-streaming
- databricks/databricks-agent-skills/plugins/databricks/cursor/skills/databricks-spark-structured-streaming
- databricks/databricks-agent-skills/skills/databricks-spark-structured-streaming
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