File Data Connector Deployment Guide

Production operating guide for the File data connector (reading files from the local or mounted filesystem).

Authentication & Secrets

The File connector has no authentication layer. Access control is enforced by the operating system:

• The Spice runtime process must have read permission on the target file or directory.
• For containers, mount source files as read-only volumes.
• For Kubernetes, prefer ConfigMap / Secret / PersistentVolumeClaim mounts over host paths.

For secrets embedded in data files (credentials, tokens), encrypt at rest and restrict filesystem ACLs to the Spice process user.

Resilience Controls

The File connector reads local files synchronously; there is no network layer, retry, or concurrency semaphore. Failures are filesystem errors (ENOENT, EACCES, EIO) and surface directly to the caller. Filesystem issues (e.g., an NFS mount going stale) must be handled at the infrastructure layer.

For hot-reloading of updated data files, accelerate the dataset and configure a refresh_interval — the connector re-reads the file on each refresh.

Capacity & Sizing

• Throughput: Bounded by local disk bandwidth. For NVMe and locally-attached SSDs, expect single-threaded reads of hundreds of MB/s for uncompressed formats and proportionally less for compressed formats due to CPU cost.
• Memory: File reads are streamed; memory footprint is bounded by DataFusion's 8192-row record batch size.
• Directory listings: Glob patterns and directory paths list the full matching set at plan time. For directories with tens of thousands of files, expect multi-second planning overhead.
• Hive partitioning: Enable hive_partitioning_enabled: true when reading partitioned directories to prune at plan time.

File Formats

See File Formats for format-specific parameters. Choose based on access pattern:

• Parquet: Best for analytical reads. Column pruning and predicate pushdown apply.
• CSV: Text-scan workloads only; set has_header and delimiter explicitly.
• JSON (newline-delimited): Good for ad-hoc reads; schema inference cost is linear in sampled records.
• Arrow IPC: Fastest for Spice-to-Spice data exchange.

Metrics

The File connector does not register connector-specific instruments. Monitor via Spice's query execution metrics (query_duration_ms, query_processed_rows). See Component Metrics for general configuration.

For filesystem-level issues (disk utilization, IOPS), use the underlying OS metrics (Prometheus node_exporter, CloudWatch agent, etc.).

Task History

File reads participate in task history through DataFusion's execution-plan spans. Listings, opens, and reads are attributed to the enclosing sql_query or accelerated_table_refresh task.

Known Limitations

• Read-only: The File connector cannot write.
• No file watching: File updates are not detected automatically; use refresh_interval on an accelerated dataset to pick up changes.
• Container portability: Hard-coded file:// paths in a spicepod are non-portable across environments; parameterize via env vars or use network-mounted paths with consistent mount points.
• Large CSVs: CSV reads are single-threaded; prefer Parquet for datasets larger than a few GB.

Troubleshooting

Symptom	Likely cause	Resolution
No such file or directory	Path typo, wrong working directory, or missing mount.	Verify the file exists from the Spice process context (ls inside the container).
Permission denied	Spice process user lacks read permission.	Adjust file ACLs or mount with appropriate UID/GID.
Schema inference is slow for JSON	Large file with sparse fields sampled.	Provide an explicit schema, or sample fewer records.
Planning time dominates for glob patterns	Very large directory listings.	Prune with Hive partitioning or break the dataset into narrower prefixes.
Query returns old data after file was replaced	No file watch; Spice sees cached schema.	Set refresh_interval on an accelerated dataset, or restart the runtime.