Spark-pipe is a tool for spark, that changes a command line program(C/C++, Java, etc.) of stand-alone version to a distributed one. Spark-pipe makes use of pipe-API to implement the computing task by preprocessing(merging) the source data and spliting it before executing spark map job. Its process flow could be showed as follows.
- clone the repo
- cd to the project directory
$ make
After compiling, there would create a build folder and get logs like this :
================================================================================
The Program has been compiled.
Location = /xxxx/spark-pipe/build/
JAVA_HOME = /xxxx/jdk1.8.0_77
HADOOP_HOME = /usr/local/hadoop
SPARK_HOME = /usr/local/spark
================================================================================
Step 1 :Modify these script according your program
- merge.sh It's a executable program you change one data unit to one string line. For example :
example_1.fastq :
@ERR000589.36 EAS139_45:5:1:2:1002/1
AATTGTCCAAGAGATTCTCACACATGTGAAAAATGACTGGTATAGAAGATT
+
IAIIIIIIIIIII.6ID5ID=<>>II+I2A.H.I;I.<09+2&06+&+)/&
example_2.fastq :
@ERR000589.36 EAS139_45:5:1:2:1002/2
TCTTCACCATTCTTTTATAGCAATACATAGTATTCCATCTTAGGCCTGTTC
+
3IIFHIIGFI1IIII<I5<7,=@F4332/D+13C58:/*//'?/')*:27.
merge.fastq
@ERR000589.36 EAS139_45:5:1:2:1002/1|AATTGTCCAAGAGATTCTCACACATGTGAAAAATGACTGGTATAGAAGATT|+|IAIIIIIIIIIII.6ID5ID=<>>II+I2A.H.I;I.<09+2&06+&+)/&|@ERR000589.36 EAS139_45:5:1:2:1002/2|TCTTCACCATTCTTTTATAGCAATACATAGTATTCCATCTTAGGCCTGTTC|+|3IIFHIIGFI1IIII<I5<7,=@F4332/D+13C58:/*//'?/')*:27.
-
split_program.py Split one line to several lines if necessary.
-
extern_program.sh
A command line program implemented using C/C++, Java, etc.
Step 2 :Run bash script
USAGE: ./build/pipe_execute.sh SPARK_MASTER HDFS_FILE HDFS_FOLDER PARTITION_NUM
Take the data & conf of current repo for example :
$ cd data
$ ../conf/merge.sh example_1.fastq example_2.fastq merge.fastq
$ hdfs dfs -copyFromLocal merge.fastq $HDFSPATH/merge.fastq
$ cd ../bin
$ ./pipe_execute.sh $HDFSPATH/merge.fastq $HDFSPATH/OUTPUT 1
- Make sure to DOWLOAD the extern programe writen in :
${ROOT_DIR}/conf/extern_program.sh
e.g.
/xxx/bwa mem -t 16 /xxx/hg19Index/hg19.fa ${LINE}
- ${LINE} actually is like "1.fastq 2.fastq". See output format of split_program.py.
- bwa download
- hg19Index download
- Make sure your conf path and extern_program can be accessed by all your computer cluster nodes if using spark cluster mode.
Apache 2.0