Tables¶

Manage SQL tables on Microsoft Fabric Data Warehouses and SQL Analytics Endpoints. Commands and tools cover listing, counting, reading, creating (including CTAS, empty DDL from schema inference, and zero-copy clone), deleting, clearing, renaming, and loading data via COPY INTO from local files or remote URLs.

Targets: Data Warehouse · SQL Analytics Endpoint

CLI¶

tables clear¶

Targets: Data Warehouse only

Truncate a table (delete all rows, keep structure). You will be asked to confirm unless --yes is passed.

Synopsis

fdw [-w WORKSPACE] tables clear [OPTIONS] [WAREHOUSE] QUALIFIED_NAME

Example

fdw -w MyWorkspace --yes tables clear SalesWH dbo.staging_load

tables clone¶

Targets: Data Warehouse only

Create a zero-copy clone of a table using CREATE TABLE … AS CLONE OF. Pass --at to clone from a point in time within the warehouse data-retention window.

Synopsis

fdw [-w WORKSPACE] tables clone [OPTIONS] [ITEM]

Example

# Clone to the current state
fdw -w MyWorkspace tables clone SalesWH \
  --source dbo.orders \
  --name dbo.orders_backup

# Point-in-time clone
fdw -w MyWorkspace tables clone SalesWH \
  --source dbo.orders \
  --name dbo.orders_may_snapshot \
  --at 2024-05-20T14:00:00

tables count¶

Targets: Data Warehouse · SQL Analytics Endpoint

Return the total row count of a table using SELECT COUNT_BIG(*).

Synopsis

fdw [-w WORKSPACE] tables count [WAREHOUSE] QUALIFIED_NAME

Example

fdw -w MyWorkspace tables count SalesWH dbo.orders

{"schema": "dbo", "name": "orders", "row_count": 999999}

tables create¶

Targets: Data Warehouse only

Create a new table on a Fabric Data Warehouse. Two modes are available:

• CTAS (CREATE TABLE … AS SELECT) — supply --select or --from-file. The body must start with SELECT (leading block/line comments are allowed).
• Empty DDL (CREATE TABLE … (col TYPE, …)) — supply one or more of --from-parquet, --from-csv, --from-schema, or --column. No data is ever read or inserted; this scaffolds the table structure only.

Synopsis

fdw [-w WORKSPACE] tables create [OPTIONS] [WAREHOUSE]

CTAS options¶

Exactly one of --select or --from-file must be provided for the CTAS path. Cannot be combined with empty-DDL options.

Empty-DDL options¶

--from-parquet, --from-csv, and --from-schema/--column are mutually exclusive with each other and with the CTAS path. For the explicit-schema path at least one --from-schema or --column must be provided.

Arrow → T-SQL type mapping (Parquet / CSV inference)

Examples

# CTAS
fdw -w MyWorkspace tables create SalesWH \
  --name dbo.orders_2026 \
  --select "SELECT * FROM dbo.orders WHERE YEAR(sale_date) = 2026"

# Empty table from Parquet schema
fdw -w MyWorkspace tables create SalesWH \
  --name dbo.sales_empty \
  --from-parquet ./exports/sales.parquet

# Empty table from CSV header (type inference)
fdw -w MyWorkspace tables create SalesWH \
  --name staging.raw_products \
  --from-csv ./data/products.csv --varchar-length 500

# Empty table with explicit inline columns
fdw -w MyWorkspace tables create SalesWH \
  --name dbo.events \
  --column "event_id:BIGINT:notnull" \
  --column "event_type:VARCHAR(100)" \
  --column "occurred_at:DATETIME2(7)"

# Explicit schema from JSON file + extra columns
fdw -w MyWorkspace tables create SalesWH \
  --name dbo.audit_log \
  --from-schema ./schemas/audit_log.json \
  --column "inserted_at:DATETIME2(7):notnull"

tables delete¶

Targets: Data Warehouse only

Drop a table. You will be asked to confirm unless --yes is passed.

Synopsis

fdw [-w WORKSPACE] tables delete [OPTIONS] [WAREHOUSE] QUALIFIED_NAME

Example

fdw -w MyWorkspace --yes tables delete SalesWH dbo.orders_2026

tables list¶

Targets: Data Warehouse · SQL Analytics Endpoint

List all tables on a warehouse or SQL Analytics Endpoint. Pass --schema to filter to a single schema.

Synopsis

fdw [-w WORKSPACE] tables list [OPTIONS] [WAREHOUSE]

Example

fdw -w MyWorkspace tables list SalesWH --schema dbo

 schema_name  name      created               modified
 ------------ --------- --------------------- ---------------------
 dbo          customers 2026-01-10T08:00:00Z  2026-06-01T12:00:00Z
 dbo          orders    2026-02-01T09:00:00Z  2026-05-15T14:00:00Z

tables load¶

Targets: Data Warehouse only

Load data into a warehouse table via COPY INTO from either a local file or a remote URL.

Local file path (--file): the file is staged to a temporary Lakehouse in OneLake (chunked DFS upload), loaded into the target table via COPY INTO, and the staging Lakehouse is automatically deleted in a finally block regardless of success or failure. JSON files are converted client-side to Parquet (requires pyarrow) before staging.

Remote URL (--url): COPY INTO is issued directly from the given URL. For OneLake or same-tenant URLs no credential is needed. For secured external URLs (Azure Blob Storage, ADLS Gen2) supply --credential-type and --secret/--identity as appropriate.

Auto-create (create-and-load) — Pass --create to auto-create the target table from the source schema before loading (local files only; requires pyarrow). The schema is inferred from the source:

• Parquet: exact types are read from the Parquet footer (no row data is read).
• CSV: the header row and up to --sample-rows rows are read for type inference. Use --all-varchar to skip inference and force every column to VARCHAR.
• JSON: the file is converted to Parquet internally (as required for staging); the schema is read from the resulting Parquet footer.

Use --if-exists to control behaviour when the table already exists:

truncate and replace are permanently destructive and require confirmation (or --yes / -y).

Use --cleanup-on-failure to drop the table if WE created it in this call and the subsequent COPY INTO fails. A pre-existing table is never dropped by this flag.

Synopsis

fdw [-w WORKSPACE] tables load [OPTIONS] [ITEM] QUALIFIED_NAME

QUALIFIED_NAME is the dot-separated schema.table_name of the destination table.

Examples

# Load a local CSV into an existing table (header row present)
fdw -w MyWorkspace tables load SalesWH dbo.sales --file data.csv

# Load a local Parquet file into an existing table
fdw -w MyWorkspace tables load SalesWH dbo.events --file events.parquet

# Load a local JSON file (converts to Parquet internally; requires pyarrow)
fdw -w MyWorkspace tables load SalesWH dbo.products --file products.json

# Auto-create the table from a Parquet schema, then load
fdw -w MyWorkspace tables load SalesWH dbo.sales --file data.parquet --create

# Auto-create from CSV, force all columns to VARCHAR
fdw -w MyWorkspace tables load SalesWH dbo.raw --file raw.csv --create --all-varchar

# Replace the existing table (drop + recreate schema + load), skip confirmation
fdw -w MyWorkspace tables load SalesWH dbo.sales --file data.parquet --create \
    --if-exists replace -y

# Auto-create; drop the table if the load fails (cleanup_on_failure)
fdw -w MyWorkspace tables load SalesWH dbo.sales --file data.parquet --create \
    --cleanup-on-failure

# Load from a remote OneLake URL (no credential needed)
fdw -w MyWorkspace tables load SalesWH dbo.orders \
    --url "https://onelake.dfs.fabric.microsoft.com/ws/lh.Lakehouse/Files/orders.parquet" \
    --format parquet

# Load from Azure Blob with SAS token
fdw -w MyWorkspace tables load SalesWH dbo.events \
    --url "https://myaccount.blob.core.windows.net/data/events.csv" \
    --format csv --credential-type sas --secret "?sv=2021&..."

tables read¶

Targets: Data Warehouse · SQL Analytics Endpoint

Read up to --count rows from a table and emit them as JSON (default), CSV, or Parquet.

CSV and Parquet formats require --output. JSON is emitted to stdout by default.

Synopsis

fdw [-w WORKSPACE] tables read [OPTIONS] [WAREHOUSE] QUALIFIED_NAME

Example

fdw -w MyWorkspace tables read SalesWH dbo.orders --count 5

[
  {"id": 1, "amount": 99.99, "customer_id": 42},
  ...
]

tables rename¶

Targets: Data Warehouse only

Rename a table via sp_rename. The new name must be an unqualified (bare) identifier — sp_rename cannot move a table to a different schema.

Synopsis

fdw [-w WORKSPACE] tables rename [OPTIONS] [ITEM] QUALIFIED_NAME

QUALIFIED_NAME is the current dot-separated schema.table_name.

Example

fdw -w MyWorkspace tables rename SalesWH dbo.orders_2025 --new-name orders_archive_2025

MCP tools¶

clear_table¶

Targets: Data Warehouse only

Truncate a SQL table (remove all rows, preserve structure).

CAUTION: This is a destructive, irreversible operation. All rows will be permanently deleted. The table structure is preserved. Confirm with the user before calling.

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse or SQL analytics endpoint name or GUID.
• qualified_name (str) — dot-separated table name, e.g. dbo.sales.

Returns: { "truncated": true } — confirmation.

clone_table¶

Targets: Data Warehouse only

Create a zero-copy clone of a table using CREATE TABLE … AS CLONE OF …. Only supported on Fabric Data Warehouses (not SQL Analytics Endpoints).

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse name or GUID.
• source (str) — qualified source table name, e.g. dbo.sales.
• new_table (str) — qualified name for the new cloned table, e.g. dbo.sales_clone.
• at (str | null, optional) — ISO-8601 UTC timestamp for a point-in-time clone (e.g. 2024-05-20T14:00:00). Must be within the data-retention window. When omitted, the clone reflects the current state of the source table.

Returns: Table — the newly-created cloned table record.

count_table_rows¶

Targets: Data Warehouse · SQL Analytics Endpoint

Return the total row count of a table via SELECT COUNT_BIG(*).

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse or SQL analytics endpoint name or GUID.
• qualified_name (str) — dot-separated table name, e.g. dbo.sales.

Returns: { "schema": str, "name": str, "row_count": int } — the schema name, table name, and total row count.

create_empty_table¶

Targets: Data Warehouse only

Create an empty SQL table from an explicit column specification (DDL only — no data is ever read or inserted). This scaffolds the table structure so that data can be loaded separately.

Server-side file access is unreliable in MCP deployments, so CSV/Parquet schema inference is not available via this tool. Use fdw tables create --from-parquet or --from-csv (CLI) for file-based schema inference.

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse name or GUID. SQL Analytics Endpoints are rejected.
• qualified_name (str) — dot-separated table name, e.g. dbo.sales.
• columns (list[object]) — non-empty list of column definitions, each an object with:
• name (str) — column identifier (must be a valid SQL identifier).
• sql_type (str) — Fabric-DW-supported T-SQL type, e.g. "INT", "VARCHAR(255)", "DECIMAL(18,2)".
• nullable (bool, optional, default true) — whether the column allows NULL.

Returns: Table — the newly-created table record.

Example call:

{
  "workspace": "MyWorkspace",
  "item": "SalesWarehouse",
  "qualified_name": "dbo.events",
  "columns": [
    {"name": "event_id", "sql_type": "BIGINT", "nullable": false},
    {"name": "event_type", "sql_type": "VARCHAR(100)", "nullable": true},
    {"name": "occurred_at", "sql_type": "DATETIME2(7)", "nullable": false}
  ]
}

create_table¶

Targets: Data Warehouse only

Create a new SQL table via CTAS (CREATE TABLE … AS SELECT).

CAUTION: select_body is executed verbatim as DDL. Confirm intent before calling. The first non-comment keyword must be SELECT.

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse or SQL analytics endpoint name or GUID.
• qualified_name (str) — dot-separated table name, e.g. dbo.sales.
• select_body (str) — the SELECT statement for the CTAS source.

Returns: Table — the newly-created table record.

delete_table¶

Targets: Data Warehouse only

Drop a SQL table.

CAUTION: This is a destructive, irreversible operation. All data will be permanently deleted. Confirm with the user before calling.

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse or SQL analytics endpoint name or GUID.
• qualified_name (str) — dot-separated table name, e.g. dbo.sales.

Returns: { "dropped": true } — confirmation.

import_table_from_url¶

Targets: Data Warehouse only

Load data from a remote URL into an existing Data Warehouse table with control over what happens when the table already has data. This tool extends load_table_from_url with an if_exists policy.

if_exists policy:

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse name or GUID. SQL Analytics Endpoints are rejected.
• qualified_name (str) — dot-separated qualified table name, e.g. dbo.sales.
• url (str) — source URL (OneLake DFS URL or external Azure Blob URL).
• file_type ("CSV" | "PARQUET") — file type to load. JSON is not supported for remote URLs.
• if_exists ("fail" | "append" | "truncate" | "replace", default "fail") — what to do when the target table already exists.
• credential_type ("none" | "sas" | "managed-identity" | "service-principal" | "account-key", default "none") — credential type for secured external URLs.
• secret (str | null, optional) — credential secret (SAS token, client secret, or account key). Never logged.
• identity (str | null, optional) — identity for managed-identity or service-principal.
• delimiter (str | null, optional) — CSV column delimiter (e.g. ,, \t).
• has_header (bool, default true) — when true, the first CSV row is a header and is skipped.
• encoding (str | null, optional) — CSV encoding (e.g. UTF8, UTF8BOM).
• field_quote (str | null, optional) — CSV field-quote character.
• row_terminator (str | null, optional) — CSV row terminator (e.g. \n, \r\n).
• max_errors (int | null, optional) — maximum errors before aborting.
• rejected_row_location (str | null, optional) — URL to write rejected rows to.

Returns: CopyIntoResult — { "rows_loaded": int, "rows_rejected": int, "target": "schema.table" }.

list_tables¶

Targets: Data Warehouse · SQL Analytics Endpoint

List SQL tables on a warehouse or SQL Analytics Endpoint.

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse or SQL analytics endpoint name or GUID.
• schema (str | null, optional) — when provided, only tables in this schema are returned.

Returns: list[Table] — each with schema_name, name, qualified_name, created, modified.

load_table_from_url¶

Targets: Data Warehouse only

Load data into a Data Warehouse table via COPY INTO from a remote URL. For OneLake or same-tenant URLs, no credential is needed. For secured external URLs (Azure Blob Storage, ADLS Gen2), supply credential_type and the appropriate secret/identity values.

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse name or GUID. SQL Analytics Endpoints are rejected.
• qualified_name (str) — dot-separated qualified table name, e.g. dbo.sales.
• url (str) — source URL (OneLake DFS URL or external Azure Blob URL).
• file_type ("CSV" | "PARQUET") — file type to load.
• credential_type ("none" | "sas" | "managed-identity" | "service-principal" | "account-key", default "none") — credential type for secured external URLs.
• secret (str | null, optional) — credential secret (SAS token, client secret, or account key). Never logged.
• identity (str | null, optional) — identity for managed-identity or service-principal.
• delimiter (str | null, optional) — CSV column delimiter (e.g. ,, \t).
• has_header (bool, default true) — when true, the first CSV row is a header and is skipped.
• encoding (str | null, optional) — CSV encoding (e.g. UTF8, UTF8BOM).
• field_quote (str | null, optional) — CSV field-quote character.
• row_terminator (str | null, optional) — CSV row terminator (e.g. \n, \r\n).
• max_errors (int | null, optional) — maximum errors before aborting.
• rejected_row_location (str | null, optional) — URL to write rejected rows to.

Returns: CopyIntoResult — { "rows_loaded": int, "rows_rejected": int, "target": "schema.table" }.

read_table¶

Targets: Data Warehouse · SQL Analytics Endpoint

Return up to count rows from a table as JSON-serialisable columns and rows.

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse or SQL analytics endpoint name or GUID.
• qualified_name (str) — dot-separated table name, e.g. dbo.sales.
• count (int, default 10) — maximum rows to return.

Returns: { "columns": list[str], "rows": list[list] } — column names and row arrays.

rename_table¶

Targets: Data Warehouse only

Rename a SQL table via sp_rename. Only supported on Fabric Data Warehouses (SQL Analytics Endpoints are rejected). The new name must be a bare (unqualified) identifier — sp_rename cannot move a table to a different schema.

Parameters:

• workspace (str) — workspace name or GUID.
• item (str) — warehouse name or GUID.
• qualified_name (str) — current dot-separated qualified table name, e.g. dbo.sales.
• new_name (str) — new bare table name (no schema prefix), e.g. sales_v2.

Returns: Table — the updated table record.