Read a Microsoft Fabric/OneLake Delta table (ADLS Gen2)

Authenticates to OneLake (ADLS Gen2), resolves the table's _delta_log to determine the current active Parquet parts, downloads only those parts to a local staging directory, and returns the result as a tibble.

Usage

fabric_onelake_read_delta_table(
  table_path,
  workspace_name,
  lakehouse_name,
  schema = NULL,
  tenant_id = Sys.getenv("FABRICQUERYR_TENANT_ID"),
  client_id = Sys.getenv("FABRICQUERYR_CLIENT_ID", unset =
    "04b07795-8ddb-461a-bbee-02f9e1bf7b46"),
  dest_dir = NULL,
  verbose = TRUE,
  dfs_base = "https://onelake.dfs.fabric.microsoft.com"
)

Arguments

table_path

Character. Table name or nested path (e.g. "Patienten" or "Patienten/patienten_hash"). Only the last path segment is used as the table directory under Tables/.

workspace_name

Character. Fabric workspace display name or GUID (this is the ADLS filesystem/container name).

lakehouse_name

Character. Lakehouse item name, with or without the .Lakehouse suffix (e.g. "Lakehouse" or "Lakehouse.Lakehouse").

schema

Character or NULL. Lakehouse schema name (e.g. "dbo"). When supplied, the table is resolved under Tables/<schema>/<table> instead of Tables/<table>. Schema support requires a schema-enabled Lakehouse (enabled by default for new lakehouses). Defaults to NULL (no schema, for non-schema lakehouses). (Note: schema support through this argument is experimental.)

tenant_id

Character. Entra ID (Azure AD) tenant GUID. Defaults to Sys.getenv("FABRICQUERYR_TENANT_ID") if missing.

client_id

Character. App registration (client) ID. Defaults to Sys.getenv("FABRICQUERYR_CLIENT_ID"), falling back to the Azure CLI app id "04b07795-8ddb-461a-bbee-02f9e1bf7b46" if not set.

dest_dir

Character or NULL. Local staging directory for Parquet parts. If NULL (default), a temp dir is used and cleaned up on exit.

verbose

Logical. Print progress messages via {cli}. Default TRUE.

dfs_base

Character. OneLake DFS endpoint. Default "https://onelake.dfs.fabric.microsoft.com".

Value

A tibble with the table's current rows (0 rows if the table is empty).

Details

• In Microsoft Fabric, OneLake exposes each workspace as an ADLS Gen2 filesystem. Within a Lakehouse item, Delta tables are stored under Tables/<table> (non-schema lakehouse) or Tables/<schema>/<table> (schema-enabled lakehouse) with a _delta_log/ directory that tracks commit state. This helper replays the JSON commits to avoid double-counting compacted/removed files.

• Schema-enabled lakehouses (the default for new lakehouses) organise tables into named schemas. Supply the schema argument (e.g. "dbo") to read a table stored under a specific schema.

• Ensure the account/principal you authenticate with has access via Lakehouse -> Manage OneLake data access (or is a member of the workspace).

• AzureAuth is used to acquire the token. Be wary of caching behavior; you may want to call AzureAuth::clean_token_directory() to clear cached tokens if you run into issues

Examples

# Example is not executed since it requires configured credentials for Fabric
if (FALSE) { # \dontrun{
df <- fabric_onelake_read_delta_table(
  table_path     = "Patients/PatientInfo",
  workspace_name = "PatientsWorkspace",
  lakehouse_name = "Lakehouse.Lakehouse",
  tenant_id      = Sys.getenv("FABRICQUERYR_TENANT_ID"),
  client_id      = Sys.getenv("FABRICQUERYR_CLIENT_ID")
)
dplyr::glimpse(df)

# Schema-enabled lakehouse: read from Tables/dbo/PatientInfo
df2 <- fabric_onelake_read_delta_table(
  table_path     = "PatientInfo",
  workspace_name = "PatientsWorkspace",
  lakehouse_name = "Lakehouse.Lakehouse",
  schema         = "dbo"
)
} # }