Apache Spark to Spotfire Integration
AI-first ETL from Apache Spark into Spotfire. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apache Spark into Spotfire
Datrise syncs Apache Spark's jobs, stages, tasks, executors, SQL queries, and application metrics into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.
Ideal for interactive analytical visualization and data science.
Endpoints
Apache Spark: Distributed engine for large-scale data processing.
Spotfire: Visual analytics platform for interactive dashboards and data science workflows.
How Apache Spark entities map to Spotfire
| Apache Spark entity | Spotfire object | Notes |
|---|---|---|
| jobs | apache_spark_jobs | id PK · custom fields → flattened columns for visualizations |
| 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 Spotfire?
Flexible values are stored as flattened columns for visualizations, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spotfire types.
How does the Apache Spark to Spotfire sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.
Related pipelines
More destinations for Apache Spark
- Apache Spark → Yellowfin
- Apache Spark → PostgreSQL
- Apache Spark → MySQL
- Apache Spark → Microsoft SQL Server
- Apache Spark → Oracle Database
- Apache Spark → Snowflake
- Apache Spark → Google BigQuery
- Apache Spark → Amazon Redshift
- Apache Spark → Databricks SQL Warehouse
- Apache Spark → ClickHouse
- Apache Spark → DuckDB
- Apache Spark → Amazon Athena
Early access
Connect Apache Spark to Spotfire 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.