Use Exasol document-file virtual schemas for federated read-only access to object and file storage — S3, Google Cloud Storage, Azure Blob Storage, and Azure Data Lake Storage Gen2 document files. Covers document-file adapter family selection, the EDML `MAPPING` definition, `CREATE VIRTUAL SCHEMA` usage, refresh workflows, and query-side troubleshooting.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Trigger when the user mentions document virtual schema, document virtual schemas, document files virtual schema, document-file virtual schema adapter, EXPLAIN VIRTUAL for document-file/object-storage virtual schema troubleshooting, S3 document files, Google Cloud Storage document files, Azure Blob document files, Azure Data Lake Gen2 document files, or Azure Data Lake Storage Gen2 document files.
Create and query a virtual schema
document files virtual schema, S3 document files, Google Cloud Storage document files, Azure Blob document files, Azure Data Lake Gen2 document files, Azure Data Lake Storage Gen2 document files, query object storagereferences/document-virtual-schemas.mdRefresh, debugging, and troubleshooting
document files virtual schema, S3 document files, Google Cloud Storage document files, Azure Blob document files, Azure Data Lake Gen2 document files, Azure Data Lake Storage Gen2 document files, REFRESH, partial refresh, connection validation, pushdown, EXPLAIN VIRTUAL for document-file/object-storage virtual schema troubleshootingreferences/document-virtual-schemas.mdChoose the right document-file adapter family
document virtual schema, document virtual schemas, document-file virtual schema, document files virtual schema, S3 document files, Google Cloud Storage document files, Azure Blob document files, Azure Data Lake Gen2 document files, Azure Data Lake Storage Gen2 document filesreferences/document-virtual-schemas.md还没有评价。欢迎分享你的使用感受。
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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.
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Exasol BucketFS file system management via the `exapump bucketfs` CLI. Covers listing, uploading, downloading, and deleting files and directories in BucketFS, the `bfsdefault` service and other bucket services, bucket structure, `bfs_*` profile settings, the `/buckets/<service>/<bucket>/<path>` UDF path, and staging JARs, models, and Script Language Containers for UDFs.
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Use Exasol Cloud Storage Extension workflows for moving structured object-storage files through extension UDFs. Covers setup prerequisites, the fixed `CLOUD_STORAGE_EXTENSION.IMPORT_PATH` and `CLOUD_STORAGE_EXTENSION.EXPORT_PATH` entrypoints used with `FROM SCRIPT` and `INTO SCRIPT`, Parquet, Avro, ORC, and Delta files on S3, Google Cloud Storage, Azure Blob Storage, Azure Data Lake, HDFS, and Alluxio, connection-object credential patterns, and routing away from native IMPORT or EXPORT when the extension path is the right fit.
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Exasol database interaction via the exapump CLI and Exasol SQL. Covers SQL queries and DML/DDL such as `SELECT`, `INSERT`, `UPDATE`, `DELETE`, `MERGE`, `CREATE TABLE`, `ALTER TABLE`, and `DROP TABLE`, `CREATE CONNECTION` connection objects without import or export intent, schema inspection, table design, `exapump sql` and `exapump profile`, query profiling, analytics, and Exasol-specific SQL behavior outside exasol-import and exasol-export.
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Distributed machine learning, data mining, and iterative HPC with Exasol. Covers end-to-end ML pipelines (DISTRIBUTE BY + SET scripts + BucketFS), per-entity federated training with partial_fit and ctx.reset(), batch inference, map-reduce ensemble training, distributed ensemble and SON algorithm for frequent itemset mining (Apriori, FP-Growth, association rules, market-basket analysis), Lua execute script orchestration for iterative algorithms (k-means, SGD, gradient descent), scikit-learn model training, parallel hyperparameter search, per-entity forecasting, anomaly detection, model lifecycle in BucketFS (pickle/joblib/ONNX versioning), GPU acceleration via CUDA SLCs (PyTorch/TensorFlow/RAPIDS), and ML-specific performance tuning (skew, OOM, multi-pass chunking).
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Use Exasol `EXPORT` and `EXPORT INTO` SQL plus `exapump export` local file workflows for moving data out of Exasol. Covers native CSV/FBV export, local CSV/Parquet exports with exapump, `CREATE CONNECTION` connection objects for export, FTP, SFTP, HTTP, HTTPS, and cloud targets on S3, Azure Blob Storage, and Google Cloud Storage (GCS), reject limits, and export credential patterns.
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