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@Ishani-10 Ishani-10 commented Oct 11, 2025

Description

Complete Spark integration with Jupyter notebook for data analysis. Includes full Docker Compose setup, configuration management, and comprehensive documentation.

Key Features

  • Spark + Iceberg REST Catalog integration
  • Interactive Jupyter notebook interface
  • MySQL to Iceberg data pipeline
  • Production-ready configuration

Fixes # (issue)

N/A

Type of change

  • New feature (non-breaking change which adds functionality)

Documentation

  • N/A (bug fix, refactor, or test changes only)

@sandipkumardey
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Hi @Ishani-10, can you please fix the PR title (use type(scope): description) and update the documentation link, or mark it as N/A and update the PR.

@Ishani-10 Ishani-10 changed the title Feature/add spark data lakehouse feat(spark): Add Spark + Iceberg playground example Oct 16, 2025
@Ishani-10
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Documentation: N/A - This adds a new self-contained example following existing patterns in the examples/ folder.

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Please do test your PR once.

In your docker-compose.yml file, your REST service still depends on postgres (which has been removed after your change). Thus, the docker compose up -d command is not even getting executed because of it.

Comment on lines +87 to +101
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Show available catalogs\n",
"print(\"Available Catalogs:\")\n",
"spark.sql(\"SHOW CATALOGS\").show()\n",
"\n",
"# Show namespaces in Iceberg catalog\n",
"print(\"\\nNamespaces in Iceberg Catalog:\")\n",
"spark.sql(\"SHOW NAMESPACES IN iceberg\").show()"
]
},
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FIx this issue, after you remove the pg dependency from the REST service, your .ipynb query fails here.

image

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3 participants