Apache Spark to Chartio Integration
AI-first ETL from Apache Spark into Chartio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apache Spark into Chartio
Datrise syncs Apache Spark's jobs, stages, tasks, executors, SQL queries, and application metrics into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.
Ideal for drag-and-drop charting over a database.
Endpoints
Apache Spark: Distributed engine for large-scale data processing.
Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.
How Apache Spark entities map to Chartio
| Apache Spark entity | Chartio object | Notes |
|---|---|---|
| jobs | apache_spark_jobs | id PK · custom fields → flattened columns for visual SQL |
| stages | apache_spark_stages | id PK · linked to apache_spark_jobs |
| tasks | apache_spark_tasks | id PK · linked to apache_spark_jobs |
| executors | apache_spark_executors | id PK · linked to apache_spark_jobs |
FAQ
How does Datrise handle Apache Spark's custom fields in Chartio?
Flexible values are stored as flattened columns for visual SQL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Chartio types.
How does the Apache Spark to Chartio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Apache Spark
- Apache Spark → Holistics
- Apache Spark → Birst
- Apache Spark → GoodData
- Apache Spark → Klipfolio
- Apache Spark → MicroStrategy
- Apache Spark → Spotfire
- Apache Spark → Yellowfin
- Apache Spark → PostgreSQL
- Apache Spark → MySQL
- Apache Spark → Microsoft SQL Server
- Apache Spark → Oracle Database
- Apache Spark → Snowflake
Early access
Connect Apache Spark to Chartio the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.