exasol-labs

Exasol database interaction via exapump CLI and Exasol SQL. Covers SQL queries, schema inspection, table design, query profiling, analytics, and Exasol-specific SQL behavior outside exasol-import and exasol-export.

Catalog and routing guide for Exasol tools, extensions, connectors, integrations, and architecture patterns. Use when users ask how to extend, customize, deploy, load, explore, enrich, surface, scale, automate, govern, migrate, or integrate Exasol, including Exasol Labs tools, AI/ML, UDFs, lakehouse, SAP, Databricks, agentic workflows, or product/version status.

Top-level router for Exasol work. Use for any Exasol database, exapump, SQL, BucketFS, extension, integration, UDF, Script Language Container, or Exasol Personal setup task, then route to the narrowest specialized Exasol skill.

Build, install, validate, and debug custom Exasol virtual schema adapters. Covers source-specific JDBC dialect implementation with virtual-schema-common-jdbc, custom document-file adapter code boundaries, JAR packaging, BucketFS deployment, adapter script setup, EXPLAIN VIRTUAL validation, and adapter-side remote debugging workflows.

Use Exasol document-file virtual schemas for federated read-only access to object and file storage. Covers document-file adapter family selection, CREATE VIRTUAL SCHEMA usage, refresh workflows, and query-side troubleshooting.

Use Exasol JDBC-based virtual schemas for federated read-only access to external databases. Covers database-source adapter selection, CREATE VIRTUAL SCHEMA, EXPLAIN VIRTUAL, metadata refresh, and query-side troubleshooting.

Use Exasol Cloud Storage Extension workflows for moving structured object-storage files through extension UDFs. Covers setup prerequisites, fixed UDF entrypoints, supported import/export formats, connection-object credential patterns, and routing away from native IMPORT or EXPORT when the extension path is the right fit.

Use Exasol IMPORT SQL plus exapump local file upload workflows for moving data into Exasol. Covers CSV, FBV, Parquet, connection objects, cloud credential patterns, reject handling, and staging-based import workflows.

Use when working on the query surface of Exasol JSON Tables in this repository. Covers wrapper views, helper schema generation, SQL preprocessor behavior, `TO_JSON(...)`, JSON helper semantics, path and array syntax, and validation of user-facing JSON-friendly SQL on the wrapper surface.

Use when implementing, debugging, or extending Exasol SQL preprocessors to customize SQL syntax, add compatibility layers, enforce query governance, build wrapper-view plus preprocessor architectures, or bridge user-facing SQL into other Exasol extension points such as virtual schemas. Covers official Exasol preprocessor APIs, upstream GitHub examples, Lua-first implementation patterns, architecture tradeoffs, and live-validation workflow.

Use when migrating MongoDB query or aggregation workloads into the Exasol wrapper-view plus preprocessor architecture in this repository. Covers MQL-to-SQL translation patterns, analytics-focused migration strategy, known wrapper strengths and limits, official MongoDB source patterns, and Nano validation workflow for ported workloads.

Use when working on the reshape stage of Exasol JSON Tables in this repository. Covers structured results, nested output materialization, structured_shape and synthesized_family authoring, durable or in-session result families, `TO_JSON(...)` as the primary final outlet, and turning relational query output back into the Exasol JSON Tables nested contract.

Use when working on the ingest stage of Exasol JSON Tables in this repository. Covers JSON or NDJSON ingestion into the source table-family contract, source-manifest generation, Exasol import flow, Rust ingest crate usage, and validation of ingest artifacts before wrapper generation.

Use when an autonomous agent needs to answer business questions through an existing Exasol Semantic Views model. Covers metric and dimension discovery, valid combination checking, structured request compilation with COMPILE_REQUEST_JSON, semantic SQL compilation including Databricks-style MEASURE()/GROUP BY ALL compatibility, result execution, plan explanation, and feedback capture. Assumes the semantic model is already built and published.

Use when an autonomous agent needs to create, bootstrap, import, or maintain an Exasol Semantic Views model. Covers schema inspection and autonomous metric derivation from physical tables, Databricks UCMV import, entity and relationship modelling, fact and dimension authoring, SQL-native metric DDL, model validation, publication, and governance configuration (agent instructions, verified queries, synonyms).

Use this to set up the Exasol Personal Local Starter Kit and run a first trusted, AI-assisted query against a local Exasol database — installing the local runtime, connecting an AI client over MCP, loading the sample data, and running the ask → inspect-SQL → run → validate → rerun loop. Triggers — "set up the Exasol starter kit", "install Exasol locally", "connect my AI to Exasol", "run my first query on my local database", "help me get started with the starter kit".

Scaffold a new CLI resource end-to-end — API client, Cobra commands, output formatting, and tests — from the OpenAPI spec.