Is there a room for improve the performance of the MD5 caculation still in SparkMD5?

[vjustin]

Is there a room for improve the performance of the MD5 caculation still in SparkMD5?

[satazor]

I think there's room for improvement, but it's not immediate. Is a process of change + bench, change + bench. Feel free to try to do some experiments and report back. I don't have the time to do it.

[brightInGit]

For the ArrayBuffer mode (FileReader.readAsArrayBuffer), why the append method needs to do the toutf8 converting with if(/[u0080-uffff]/.test(str)) { unescape(encodeURIComponent(str)) }. If I understand correctly, this will convert a byte (which is not in the range of the readable character) into something else. This looks consuming a lot of cpu. Can the "appendBinary" method be called directly instead of this "append" method? However, the hash calculating will call substring method. Will the hash rely on that the input is string? Thanks ahead for shedding some lights on this.

[brightInGit]

For the toutf8 method, the comment means the input will be converted if it is string. However, the implementation as shown below is to convert the byte array into something else if it is NOT string.
if (/[\u0080-\uFFFF]/.test(str)) {
str = unescape(encodeURIComponent(str));
}

[satazor]

If you are using FileReader.readAsArrayBuffer, you should be using https://github.com/satazor/SparkMD5#sparkmd5arraybufferappendarr which does not do any conversion.

[brightInGit]

Thank you for the explanation. I wrongly missed the ArrayBuffer.prototype.append method.

[satazor]

Performance was improved by #41. Feel free to reopen this if necessary.