--- cuppy_hub: salesforce cuppy_path: reference/official/data360/data-cloud-query-guide/references/dc-sql-reference/external-location.md cuppy_section: docs cuppy_doc: 16X3-AZQA cuppy_doc_uuid: a674bfe5-801a-40c9-bf22-abc653ef47f0 cuppy_permalink: https://cuppy.io/salesforce/d/16X3-AZQA cuppy_version: 1 cuppy_updated: 2026-10-23T16:16:52.575Z cuppy_canonical: https://cuppy.io/salesforce/docs/reference/official/data360/data-cloud-query-guide/references/dc-sql-reference/external-location cuppy_mcp: https://cuppy.io/mcp cuppy_body_sha256: 7c13e059cc0fcbe4181546c9838ff6e205beecba596e16067e303872be0d55f3 # cuppy_body_sha256 is over the document body ALONE, excluding both generated blocks. --- > Mirror of (Salesforce, Data 360 Query Guide), read 2026-10-23. Salesforce's own page is the authority; this copy exists because that site refuses non-browser readers. ## External Locations **Applies to:** ❌ Data 360 SQL ✅ Tableau Hyper API To specify the location where external data is read, use one of: This location can be a path in the file system of the Hyper server (not the client!) or an Amazon S3 URI. For example, `s3://mybucket/path/to/myfile.csv`. Using a file system path instructs the server to directly read from a file. The files must reside on or be accessible to the database server machine, not the client. They must be accessible to and readable by the user, not the client. The name must be specified from the viewpoint of the server. In the case of an Amazon S3 URI, you can use the extended syntax `s3_location(...)` to specify credentials and optionally a bucket region. The specified credentials can be empty if used for buckets with anonymous access. If no bucket region is specified, Data 360 SQL infers the bucket region. In this case, the specified credentials must have permissions for the `HeadBucket` S3 request. Data 360 SQLs read capabilities from Amazon S3 are highly optimized. They use techniques such as concurrent requests, request hedging, and prefetching. For maximum performance, ensure a high network bandwidth to Amazon S3. For example, run Data 360 SQL on an AWS EC2 instance. To access data stored on Microsoft Azure Blob Storage, use the `azure_location` syntax. Data 360 SQL supports the `DFS` and `BLOB` endpoints and supports these Azure URL formats. * `abfss://@/...` * `https://account.dfs.core.windows.net/container/...` * `https://account.blob.core.windows.net/container/...` * Hyper supports the non-SSL version of the URLs `http://` and `abfs://`, and it establishes SSL encrypted connections. The `ARRAY[ [, ...] ]` syntax can be used to read rows from multiple source locations. Rows are read from all source locations, and the union of all rows from all input files will be returned. All source locations in this list must share the same file format. The list can contain S3 locations, local files, or any other file locations. Don’t mix different external formats in one invocation of `external` or in one external table. To scan data from different formats at the same time or to scan data in the same format but with different format options, use one `external` function or external table per format and combine the results with `UNION ALL`. This example combines two parquet files with two CSV files. The two parquet files can be scanned with one invocation of `external`. The CSV files have a different schema and different delimiters, so they’re scanned separately. The example combines `'products4.csv'` with the rest, even though it has an additional column `discount`, because this column isn’t selected. --- You are reading one file. The same content is free over MCP at https://cuppy.io/mcp with no signup: ranked search across all 376 documents in this hub, the merged view when you work in a layer, known workarounds matched to the error you hit, and depth control so you spend tokens on what you need. Start with the `_hello` tool. How to connect: https://cuppy.io/salesforce/ Something wrong in this document? Report it with the `session feedback` tool on the same endpoint.