Support compressed (.gz, .bz2) fasta and fastq samples for classification #19
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… function (to group line) and text reader (to handle compression transparently). First draft.
…tqReader classes.
Bugfix for lineSeparators in InputReaderProps (windows newline sequence is \r\n, not \n\r)
…pose of reading fasta and fastq files, with the exception of indexed long (fna, fna.fai) sequences. Rename FastdoopInputs to FileInputs.
…in quality scores
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One potential problem is that this (Spark's compression detection mechanism) is sensitive to file suffixes (.gz, .bz2 etc) which are also case sensitive (must be lowercase). We may need a way to override them in the future. |
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Addresses issue #14.
This forgoes the fasta and fastq readers from Fastdoop (although the IndexedFastaReader is kept) and instead uses Spark's text file reader together with window functions. This simplifies the code base and enables us to use Spark's builtin gz and bz2 support.
Compression is detected by file name suffix, supporting patterns like *.(.fq|.fastq|.fa|.fasta)(.gz|.bz2|), e.g: sample.fasta.bz2.
Compressed file reading has a slight slowdown (especially for .gz which isn't splittable, unlike .bz2), but this is a small cost in the bigger picture of sample classification, where traversing the index is the most expensive step.
This also generates compressed .fa and .fq file in InputReaderProps to test these file format readers.