Open danergo opened 4 years ago
The problem is that base64_encode
put padding in the middle of the stream ('==').
Hey, thanks for the report. I'm a bit baffled by this, because like you say, if the library is run inside a mutex, it should be threadsafe. In fact, it should be fairly threadsafe to start with, because the only shared mutable datastructure it uses is the codec selection structure, which is written to once on the first call. All the other functions are reentrant and do not share common data. So that can't really explain the bug.
The padding is written by base64_stream_encode_final
, just before base64_encode
returns. So I don't see a way in which it can insert those characters into the middle of a stream. What kind of IO is writeOutput
doing? It could be that the IO is not properly flushed between threads, causing the output to be interleaved.
Before unlocking the mutex, writeOutput
adds header and trailer to the base64 data, and sends out through a socket. Now if there were incorrect flushing between threads, it shall be "all-or-nothing" fashion because of the mutex.
I'm not seeing this:
HEADER#(BASE64_1)#TRAILER HEADER#(BASE64_1)(BASE64_2)#TRAILER
But I'm seeing this:
HEADER#(BASE64_1)#TRAILER HEADER#(BASE64_2)(BASE64_3)#TRAILER
This can be easily worked around by splitting the stream at the decoder (or if there is no padding in the middle no need to split at all).
My only concern here is buffer size: I've optimized Base64Buffer
to fit 4096 bytes.
Obviously it wont be able handle more data and could cause a segfault.
I'm using this library on an ARM embedded system.
I have a static function which is called from multiple threads in the same time. I'm using boost's mutex to make the important parts atomic:
It is working, however sometimes when writeOutput is called from different threads at the same time, base64_encode creates an invalid stream.
Here is a sample invalid base64 (unfortunately I don't have the raw unencoded data):
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
Could you help me with hunting this?
How can multithread affect base64 generation if it's in an atomic mutex block?