「spark」の検索結果

Create a new component in the Modules folder from template with proper documentation and placeholders replacement.

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Launch some action to push the code in git

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Launch some action before create push in git

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Update the CHANGELOG.md with the description of the changes between the last released version and the new one

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Discovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).

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Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).

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Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).

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ScalarDB Analytics設計エージェント - ScalarDB Analyticsを使用した分析基盤の設計。Apache Sparkベースの分析クエリ、マルチDB横断分析を策定。/design-scalardb-analytics [対象パス] で呼び出し。

ScalarDB Analytics設計エージェント - ScalarDB Analyticsを使用した分析基盤の設計。Apache Sparkベースの分析クエリ、マルチDB横断分析を策定。/design-scalardb-analytics [対象パス] で呼び出し。

NVIDIA Sync デスクトップアプリのリファレンス。DGX Spark, DGX Station, 汎用 SSH Linux ホストへのリモート接続管理。mDNS 自動検出, 手動 IP 登録, SSH config インポート, Tailscale 連携, 自動ネットワーク切替。 Cluster Assistant, ConnectX-7 クラスタトポロジ, netplan 設定検証。 VS Code, Cursor, VS Code Insiders, NVIDIA AI Workbench 起動, カスタムアプリ登録, ポートフォワード, SSH トンネル。

Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).

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Notion-style team dashboard rendered as a Live Artifact. A single-page, self-contained HTML dashboard with KPIs, a 7-day sparkline, a real-time activity feed and a linked-database task table — wired to Notion via the Composio connector catalog. Refreshes on demand and when the artifact is opened. Falls back to seeded mock data when no connector is bound, so it works offline / in screenshots / in the picker preview.

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Team-management dashboard skill in the FlowAI aesthetic — three tabs (Team Members, Team Details, Activity Log), KPI stat row, member table, role distribution bar chart, online presence and activity sparklines, and a top-contributors panel, all in a single self-contained HTML file with light/dark theming, hoverable chart tooltips, click-to-zoom panels, and CSV export. Use when the brief asks for a team / workspace admin dashboard, an interactive admin dashboard with charts, or names FlowAI.

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Retrieve real-time equity, index, and ETF quotes with price, change, and sparkline history. Use when the user asks for current market prices, how a ticker is doing, or a quick market snapshot.

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Use this skill whenever you are about to create ANY chart, graph, plot, dashboard, or data visualization, in ANY output medium — an HTML or React artifact, inline SVG, plotting code in any library (matplotlib, plotly, d3, Recharts, …), an image/PNG you will render and upload, or a chart shared into Slack. Read it BEFORE writing the first line of chart code, choosing chart colors, building a stat tile / meter / KPI row, or laying out a dashboard. When the destination is a first-party document connector (host-designated, never self-described) that renders live charts, hand it the rows (inline, or as an uploaded data file the chart cites) rather than a rendered PNG/SVG — a picture of a chart loses hover, data inspection and per-value comments. Produces visualizations that read as one system — elegant, accessible, consistent in light and dark — using a brand-neutral placeholder palette you swap for your own. Teaches a design-system-agnostic method: a form heuristic, a color formula with a runnable validator, mark specs, and interaction rules. A validated default palette is documented in `references/palette.md` — swap that file's values for your brand's. Triggers on: "chart", "graph", "plot", "data viz", "visualization", "dashboard", "analytics", "visualize data", "categorical colors", "sequential / diverging palette", "stat tile", "sparkline", "heatmap", "legend", "axis", "tooltip", "chart colors", "color by series".

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Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms.

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Use this skill to build a multi-element Excel dashboard — Dashboard sheet on open, multiple formula-driven KPI cards, multiple charts, sparklines, and conditional formatting — from CSV or tabular input. Trigger on: 'dashboard', 'KPI dashboard', 'analytics dashboard', 'executive dashboard', 'metrics dashboard', 'CSV to dashboard', 'data visualization'. Output is a single .xlsx. Scene-layer on officecli-xlsx: inherits every xlsx hard rule. DO NOT invoke for: a single budget tracker / one-sheet CSV-with-formatting (use xlsx), a 3-statement / DCF / LBO financial model (use financial-model), a weekly report with at most 1 chart and fewer than 10 rows (use xlsx).

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Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues.

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Data pipeline expert for ETL, Apache Spark, Airflow, dbt, and data quality

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Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'.

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Audit TikTok Ads measurement, Pixel and Events API, mobile-first creative, audiences, Smart+, Shop and commerce campaigns, bidding, budgets, pacing, attribution, and policy. Use for TikTok Ads, TikTok Pixel, Events API, Smart+, TikTok Shop Ads, GMV Max, Spark Ads, or TikTok campaign optimization.

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Create, convert, read and edit Office documents locally with GenOffice's command line. Build a new presentation (pptx) from a brief through a checked outline, per-page spec and render pipeline, a new spreadsheet (xlsx) from CSV or JSON data with formulas, a new Word document (docx) from Markdown or HTML, or a PDF; convert between pdf, docx, xlsx, pptx, md, html and csv; read the structure and text of an existing file (including the user's own docx / xlsx / pptx as source material) and apply structured edits to it. Use whenever the user asks for a slide deck, presentation, spreadsheet, workbook, report, Word document or any real Office file, a format conversion, a rewrite of part of an existing document, or wants the result opened in the GenOffice editor. Documents are processed locally; only search, image and media send the query or the referenced file to the provider configured in GenOffice.

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Notion 风团队仪表板, KPI + 7 日 sparkline + activity feed + 任务表

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Guides understanding and working with Apache Beam runners (Direct, Dataflow, Flink, Spark, etc.). Use when configuring pipelines for different execution environments or debugging runner-specific issues.

日本語の概要は準備中です。原文の説明を表示しています。