Optimizing Dd Performance: Finding The Best Block Size For Faster File Copies

What is Block Size and Why it Matters for dd

The block size in dd determines how much data is read and written at a time. Specifically, it refers to the chunk size that dd uses when copying data from the input file to the output. Choosing an optimal block size can have a dramatic impact on dd performance.

With a larger block size, dd can copy larger chunks of data at once, minimizing overhead and streamlining the transfer. However, if the block size is set too large, it can negatively impact performance as well, especially when copying smaller files.

Definition of block size

The dd block size refers to the buffer size that specifies the amount of bytes dd reads and writes at a time. For example, a block size of 2MB tells dd to copy 2MB of data at a time from the input file before writing it to the output.

The default block size depends on the operating system, but is often quite small (512 bytes on Linux). While using a small block size minimizes wasted disk space when copying sparse or partially filled files, it adds significant I/O overhead compared to larger block sizes.

How it impacts dd copy speed

The dd block size directly affects how often dd needs to perform I/O operations to copy data. With a block size of 512 bytes, dd needs to perform twice as many read and write operations compared to a 1KB block size when copying the same file.

Higher I/O density results in greater overhead, as additional CPU and memory resources are consumed tracking each I/O operation. Consequently, larger block sizes typically allow dd to achieve much faster copy throughput.

However, if the block size is set considerably larger than the source or target disk, excessive caching can reduce performance. Finding the ideal block size depends on your specific hardware setup.

Choosing the Optimal Block Size

Selecting the most effective block size for a dd operation depends on several key factors:

• Source drive type (HDD vs SSD)
• Target drive type
• File size
• File system

Additionally, mathematical formulas can provide general guidelines for an appropriate starting block size, which can then be fine-tuned through benchmarks.

Factors to consider

Source drive type

If the input file resides on a HDD, performance is limited by disk RPM and seek times. Larger block sizes up to 2MB help minimize latency by allowing more sequential access.

For SSDs, reduced seek penalties allow for more flexibility. But block size should still align with page sizes – often 4-16KB for SSDs.

Target drive type

The capabilities of the output target drive also dictate optimal block size. Slower HDDs benefit from larger blocks up to 1-2MB, while faster SSDs can utilize smaller chunk sizes.

If both drives are fast NVMe SSDs, very large block sizes provide diminishing returns and introduce caching inefficiencies. 4-16KB is more prudent.

File size

The total size of the file(s) being copied also affects suitable block size due to caching constraints. With files smaller than available RAM, large blocks up to the total file size can maximize I/O performance.

But extremely large block sizes can overload memory when copying massive files. 1-8MB provides a sensible starting target for very large file copies.

File system

Certain file systems work better with specific block sizes due to default cluster sizes or journaling optimizations. ExFAT and NTFS perform best at 4KB or multiples of it, while XFS favors 1MB block sizes.

If copying a device endpoint to endpoint, matching the source file system block size ensures optimum compatibility.

Formulas for calculation

While the optimal block size depends greatly on your hardware, source data properties, and use case, some general formulas help provide an appropriate starting point for benchmarking:

• HDD to HDD: 2MB
• SSD to SSD: 16KB
• HDD to SSD: 1MB
• SSD to HDD: 4KB

More complex formulas factoring in the source device maximum throughput, target device write speed, and total transfer size can provide refined block size estimates to guide testing.

Example calculations

For example, consider copying a 25GB MySQL database backup from an HDD capable of 180MB/s sequential reads to an SSD supporting 550MB/s writes. Using the formula for HDD to SSD transfers, we get an initial block size estimate of:

Block size = Total size (25600 MB) x Read speed (180 MB/s) / Write speed (550 MB/s) = 0.84 MB

Rounding up slightly, a good starting block size for testing would be 1 MB. As this falls within the ideal range for the HDD source per its performance limits, using benchmarks we can fine-tune around 1 MB to find the best fit block size.

Benchmarking Block Size Performance

While mathematical predictions help select an appropriate starting block size, running benchmarks allows fine-tuning the parameter for maximum throughput.

Useful commands for assessing dd copy speed include dd itself, sync, time, and iostat. Monitoring disk utilization during transfers also provides insight.

Test methodology

An effective testing methodology involves:

1. Establishing an initial realistic block size based using your hardware capabilities
2. Copying a test file matching production data using dd, varying the block size in increments
3. Timing total transfer duration with the Unix time command
4. Calculating copy throughput by dividing total bytes copied by duration
5. Charting block size vs. throughput to determine optimal setting

Using Unix benchmarks

In addition to dd, Linux provides built-in tools to test disk performance for a given block size:

• sync – Forces cached writes to disk to measure true write speeds
• iostat – Reports detailed storage metrics and utilization info
• time – Outputs precise command runtime for speed calibration

Using these commands in conjunction with dd allows accurately benchmarking performance.

Monitoring with iostat

The utility iostat enables monitoring disk activity during transfers. By capturing metric data points at one second intervals, you can visualize throughput variability.

Metrics to analyze include:

• MB/s – Overall throughput rate
• %util – Device utilization percentage
• avgqu-sz – Average queue length of I/O requests

Span spikes may indicate suboptimal block size while stable maximum device utilization demonstrates peak speed.

Results analysis

Once benchmarking finishes, analyze the output data. Look for the highest overall write throughput speeds demonstrating maximum yet stable disk utilization.

The optimal block size likely resides close to the peaks in performance. However, also consider potential outlier data points caused by caching or competing workloads.

Chart speed vs. block size to visualize trends, honing in on size ranges with the best speeds while minimizing outliers.

Tuning Block Size for Specific Use Cases

Depending on the specific dd copy use case – the optimal block size can vary significantly. Tailor testing to these core scenarios:

Cloning drives

For direct whole drive copies, large block sizes of 1-2MB+ typically prove most efficient. Test adjustments on both sides of OS defaults.

Creating disk images

When saving disk image files, moderate block sizes of 512KB-1MB offer versatility. Align to source file system clusters.

Copying VM images

Tune VM image copies and migrations for smoothness via small blocks from 256-512KB. Conservative sizes prevent timeout penalties.

Transferring large files

For individual large file transfers, pad estimated size by 25% as a starting block figure for carving excess overhead.

Recommended sizes for each

Use Case	Starting Block Size
Drive Cloning	2MB
Disk Images	512KB-1MB
VM Images	256KB-512KB
Big Files	25% over estimated

Achieving Maximum dd Throughput

While tuning block size provides major dd speed gains, additional optimizations further maximize throughput:

Hardware considerations

Use enterprise grade SSDs, NVMe interfaces, RAID arrays, and multipath connections where possible to multiply device capabilities.

Operating system tuning

Adjust system settings like swappiness, elevator algorithm, and disk caching policies to complement high speed dd disk copies.

Leveraging async I/O

Passing the O_DIRECT flag minimizes caching for true async throughput closer to device limits.

Using multiple threads

Launch parallel dd processes splitting data segmentation evenly across drives for combined speed gains.

With optimized block size and complementary system tuning, administering lightening fast dd file copies is achievable.