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Found 114 Skills
Only to be triggered by explicit super-swarm-spark commands.
Only to be triggered by explicit /parallel-task-spark commands.
Implements Syncfusion Flutter Spark Charts (SfSparkLineChart, SfSparkAreaChart, SfSparkBarChart, SfSparkWinLossChart) for compact, lightweight data visualization. Use when working with micro charts, sparklines, KPI indicators, or inline trend charts in Flutter dashboards. This skill covers chart configuration, data binding, markers, tooltips, and trackball for all four spark chart types.
Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.
Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. Invoke for DataFrame API, Spark SQL, RDD operations, performance tuning, streaming analytics.
Complete guide for Apache Spark data processing including RDDs, DataFrames, Spark SQL, streaming, MLlib, and production deployment
Pyspark Transformer - Auto-activating skill for Data Pipelines. Triggers on: pyspark transformer, pyspark transformer Part of the Data Pipelines skill category.
Manage the full lifecycle of Alibaba Cloud EMR Serverless Spark workspaces—create workspaces, submit jobs, Kyuubi interactive queries, resource queue scaling, and status queries. Use this Skill when users want to create Spark workspaces, submit Spark jobs, view job status and logs, execute SQL via Kyuubi, scale resource queues, or view workspace status. Also applicable when users say "create a Spark workspace", "submit Spark job", "run PySpark", "execute SQL via Kyuubi", "scale resource queue", "view job logs", etc.
Apache Spark distributed computing. Use for big data processing.
Develops and executes Spark code on Dataproc Clusters and Serverless. Reads and writes data using BigLake Iceberg catalogs, BigQuery and Spanner. Debugs execution failures. Use when: - Writing Spark ETL pipelines on GCP. - Training or running inference with ML models with spark on GCP. - Managing Spark clusters, jobs, batches, and interactive sessions. Don't use when: - Writing generic Python scripts that don't use Spark. - Performing simple SQL queries that can be done directly in BigQuery.
Implement Syncfusion Angular Sparkline component for compact data visualization. Use this skill whenever the user needs to create sparkline charts, visualize small datasets inline, add markers or data labels, implement different sparkline types (Line, Column, Area, Pie, Win-Loss), or handle sparkline customization like tooltips, axis settings, and theme styling. Covers installation, basic rendering, type selection, marker configuration, data label formatting, advanced features, accessibility, and migration from EJ1.
Automate Sendspark tasks via Rube MCP (Composio). Always search tools first for current schemas.