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This PR introduces vectored read support in the Azure Blob File System (ABFS) driver to improve read performance for workloads that issue multiple small, non-contiguous read requests.
Vectored reads enable batching of multiple read ranges into fewer network calls, reducing request overhead and improving throughput—especially beneficial for analytics engines like Spark.
Current ABFS read implementation performs sequential, independent read operations for each requested range. This leads to:
Increased number of network calls
Higher latency for small/random reads
Inefficient utilization of bandwidth
Vectored I/O addresses these issues by coalescing multiple read requests into a single or fewer backend calls.
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This PR introduces vectored read support in the Azure Blob File System (ABFS) driver to improve read performance for workloads that issue multiple small, non-contiguous read requests.
Vectored reads enable batching of multiple read ranges into fewer network calls, reducing request overhead and improving throughput—especially beneficial for analytics engines like Spark.
Current ABFS read implementation performs sequential, independent read operations for each requested range. This leads to:
Increased number of network calls
Higher latency for small/random reads
Inefficient utilization of bandwidth
Vectored I/O addresses these issues by coalescing multiple read requests into a single or fewer backend calls.