CN103150161A - Task encapsulation method and device based on MapReduce computation module - Google Patents
Task encapsulation method and device based on MapReduce computation module Download PDFInfo
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Abstract
The invention relates to a task encapsulation method and device based on a MapReduce computation module. The method includes the steps of acquiring an input program, judging whether the input program is a Java compiler, if yes, packing the input program into a task with a Java job type, namely, using a Java standard packer to encapsulate the Java compiler into a Jar-formatted document, and transferring the information of the task with the Java job type to a shell task; otherwise, judging whether the input program is a program with a streaming job type; if yes, taking the program with the streaming job type as a task with the streaming job type, and transferring the information of the task with the streaming job type to the shell task; or otherwise, encapsulating the input program into a task with the streaming job type, and transferring the information of the task with the streaming job type to the shell task. The task encapsulation method and device supports more computing types, more attention can be paid on business logic instead of bottom layer encapsulation of computing tasks when practical problems are solved, and practical production requirements can be met faster and better.
Description
Technical field
The present invention relates to the cloud computing field, be specifically related to a kind of task method for packing and device based on the MapReduce computation model.
Background technology
Hadoop is one can carry out to mass data the software frame of distributed treatment, and the user can be in the situation that do not understand distributed bottom details, the exploitation distributed program.Take full advantage of power high-speed computation and the storage of cluster.Hadoop has realized a distributed system (Hadoop Distributed File System is referred to as HDFS).HDFS has the characteristics of high fault tolerance, and design is used for being deployed on cheap hardware, and its data of providing high transmission rates to visit application program, and being fit to those has the application program of super large data set.HDFS has relaxed the requirement of portable operating system interface (Portable Operating System Interface of Unix is abbreviated as POSIX), like this can be with the data in the form access file system of stream.
MapReduce is one of core component of Hadoop, and Hadoop comprises two parts, the one, and distributed file system, one one is distributed computing system, MapReduce namely, both are indispensable.That is to say, can be easy to carry out distributed calculation and programming on the Hadoop platform by MapReduce.The skeleton code of Hadoop platform is write by Java language, and therefore, the MapReduce computation model can directly be loaded and call for primary java applet.But the program for other language can't directly be called, and can only outside it, carry out write and read to the data of its input and output in the mode of data stream.The form of this data stream can be called stream operation (Streaming Job) in program.Wherein stream (Streaming) just refers to the form of inputoutput data.These data refer generally to the various executable programs under Linux: include but not limited to Linux shell (Shell program), Python or Perl program the shell script file, use the program of other language compilation, using the executable file of exporting after the compiling of Linux compiler, is some files of exe, bin as suffix.
During MapReduce computation model environment, the self-defining service logic of user program is encapsulated in the shell task that distributed computing system carries, guides whole workflow by the shell task.During MapReduce computation model environment, Java program compiler in the support of operation MapReduce computation model, use Java standard packing device that the Java program compiler is packaged into the Jar formatted file, form the task of Java homework type, then with the mission bit stream of Java homework type, namely the positional information of Jar formatted file passes to the shell task as parameter.
In computer program, task refers in multiprogram or multi-process environment, first by the groundwork that computing machine is completed, it is one or more instruction sequences of control program, the shell task refers to according to the exploitation of the self-defining development interface of MapReduce computation model, is used for the program of other programs of encapsulation.
The user is in the exploitation distributed computing system, diversified computation requirement is often arranged, need to use other language compilation programs except Java language, and the MapReduce computation model is based on the Java language exploitation, do not support for the program that other computer programming languages are write, limited dirigibility and the adaptability of whole distributed computing system.
Summary of the invention
The technical matters that the present invention will solve is that MapReduce computation model of the prior art is based on the Java language exploitation, do not support for the program that other computer programming languages are write, limit dirigibility and the adaptive technical matters of whole distributed computing system, thereby provide a kind of homework type that non-MapReduce is supported to be encapsulated as task method for packing and the device based on the MapReduce computation model of the task type of MapReduce support.
For solving the problems of the technologies described above, the technical solution used in the present invention is as follows:
A kind of task method for packing based on the MapReduce computation model comprises the steps:
S1, task engine obtains loading routine, judges that whether described loading routine is the Java program compiler that the MapReduce computation model is supported, if, execution in step S2; If not, execution in step S4;
S2 uses Java standard packing device that the Java program compiler is packaged into the Jar formatted file;
S3 passes to the positional information of Jar formatted file the shell task of moving in the MapReduce computation model;
S4 judges whether described loading routine is the program of stream homework type, if, execution in step S5; If not, execution in step S6;
S5, program that will the stream homework type is as the task of stream homework type, and the mission bit stream that will flow homework type passes to the shell task of moving in the MapReduce computation model;
S6 is encapsulated as described loading routine the task of flowing homework type, and the mission bit stream that flows homework type is passed to the shell task of moving in the MapReduce computation model.
In described step S1, judge that whether described task is the Java program compiler that the MapReduce computation model is supported, comprises the steps:
S101 according to the interface standard of MapReduce computation model definition, tests described loading routine, if return to normal data, determines that described loading routine is the Java program compiler that the MapReduce computation model is supported; Otherwise, determine that described task type is not the java applet compiling file that the MapReduce computation model is supported.
In described step S6, described loading routine is encapsulated as the task of stream homework type, comprise the steps:
S601, described loading routine is saved in distributed computing system, and described loading routine log-on message is passed to described shell task, with described loading routine and the log-on message task as the stream homework type, when described shell task call should be flowed the task of homework type, carry out loading routine by the described log-on message of calling this stream homework type task.
Described stream homework type comprises the executable program under the Linux environment.
Executable program under described Linux environment comprises the executable file of Linux shell, Python or Per l shell script, computer program output after compiling.
The log-on message of the task of described stream homework type comprises the call instruction information of the task of described stream homework type.
Based on same inventive concept, the present invention also provides a kind of task packaging system based on the MapReduce computation model, comprises that the first judge module, packetization module, first are transmitted module, the second judge module, second transmits module and package module;
Wherein,
Described the first judge module is used for obtaining loading routine, judges whether described loading routine is the Java program compiler that the MapReduce computation model is supported;
Described packetization module is used for described input being packaged as the task of Java homework type when described loading routine is the Java program compiler of MapReduce computation model support, namely uses Java standard packing device that the Java program compiler is packaged into the Jar formatted file;
Described first transmits module, is used for the mission bit stream of described Java homework type is passed to the shell task that the MapReduce computation model moves;
Described the second judge module is used for judging whether described loading routine is the program of stream homework type;
Described second transmits module, is used for the mission bit stream of described stream homework type is passed to the shell task that the MapReduce computation model moves;
Described package module is used for described loading routine is encapsulated as the task of flowing homework type, and the mission bit stream that flows homework type is passed to the MapReduce computation model.
Described the first judge module comprises the test submodule;
Wherein,
Described test submodule is used for the interface standard according to the definition of MapReduce computation model, and described loading routine is tested.
Described package module comprises the transmission submodule;
Wherein,
Described transmission submodule is used for the task of described stream homework type is saved in distributed computing system, and the task start information of described stream homework type is passed to described shell task.
Described stream homework type comprises the executable program under the Linux environment.
Executable program under described Linux environment comprises the executable file of Linux shell, Python or Per l shell script, computer program output after compiling.
Task packaging system according to claim 11 is characterized in that, the log-on message of the task of described stream homework type comprises the call instruction information of the task of described stream homework type.
Technique scheme of the present invention has the following advantages compared to existing technology:
A kind of task method for packing and device based on the MapReduce computation model of the present invention, at first, judge whether loading routine is the Java program compiler of MapReduce computation model support or the program of stream homework type, if, for the Java program compiler, loading routine is bagged directly into the task of Java homework type, the procedure operation of stream homework type is flowed the task of homework type, directly called by user program; Otherwise described loading routine is encapsulated as the task of stream homework type, will flows homework type task start information and pass to the shell task.The present invention encapsulates the program of non-Java language compiling, makes the MapReduce computation model support the program of non-Java language compiling, has satisfied the diversified computation requirement of user; The present invention supports more compute type, when solving practical problems, can more focus on service logic but not to the encapsulation of the bottom of calculation task, solves the actual production demand faster and betterly.Shell task used in the present invention includes the self-defining service logic information of storage address information, log-on message and user program of task, circulation that can control program, thus satisfy the computation requirement of user's complexity.
The code of stream homework type task is kept in described distributed computing system, and the log-on message of the task of described stream homework type is passed to described shell task, controlled the circulation of whole program by described shell task, this packaged type, simply be easy to realize, the size of code of increase is less.Described distributed computing system only need to be sent call instruction and get final product, and need not be concerned about the task code of described stream homework type by which kind of computer programming language is write when calling the task of described stream homework type.
Description of drawings
For content of the present invention is more likely to be clearly understood, the below according to a particular embodiment of the invention and by reference to the accompanying drawings, the present invention is further detailed explanation, wherein:
Fig. 1 is that embodiments of the invention one are based on the schematic flow sheet of the task method for packing of MapReduce computation model;
Fig. 2 is the schematic diagram based on the task packaging system of MapReduce computation model of embodiments of the invention two.
Embodiment
Embodiment one:
Referring to Fig. 1, a kind of task method for packing based on the MapReduce computation model of embodiments of the invention comprises the steps:
S1, task engine obtains loading routine, judges that whether described loading routine is the Java program compiler that the MapReduce computation model is supported, if, execution in step S2; If not, execution in step S4;
S2 is packaged as described loading routine the task of Java homework type, namely uses Java standard packing device that the Java program compiler is packaged into the Jar formatted file;
S3 passes to the mission bit stream of Java homework type the shell task of moving in the MapReduce computation model;
S4 judges whether described loading routine is the program of stream homework type, if will flow the task of the program of homework type as the stream homework type, execution in step S5; If not, execution in step S6; The program of described stream homework type comprises the executable program under the Linux environment; Executable program under described Linux environment comprises the executable file of Linux shell, Python or Per l shell script, computer program output after compiling;
S5 passes to the mission bit stream that flows homework type the shell task of moving in the MapReduce computation model;
S6 is encapsulated as described loading routine the task of flowing homework type, and the mission bit stream that flows homework type is passed to the shell task of moving in the MapReduce computation model; Described loading routine in this step refers to the computer program program that the computerese except Java is write, the task of described loading routine being encapsulated as the stream homework type specifically refers to described loading routine is compiled into executable program in (SuSE) Linux OS, and the executable program after then compiling and the log-on message of this executable program are packaged into stream as the task of type.
In described step S1, the Java program compiler that described MapReduce computation model is supported is exactly the program file that java applet forms after compiling, expansion .class by name.
Further, in described step S1, judge that whether described task is the Java program compiler that the MapReduce computation model is supported, comprises the steps:
S101 according to the interface standard of MapReduce computation model definition, tests described loading routine, if return to normal data, determines that described loading routine is the Java program compiler that the MapReduce computation model is supported; Otherwise, determine that described task type is not the java applet compiling file that the MapReduce computation model is supported.
Further, described loading routine is encapsulated as the task of stream homework type, comprises the steps:
S601 is saved in distributed computing system with the task of described stream homework type, and the log-on message of the task of described stream homework type is passed to described shell task.
Further, in described step S2, the mission bit stream of Java homework type comprises storage address information and the data type information of described task; The log-on message of the task of described stream homework type comprises the parameter information of setting in call instruction information, address information and the task of task of described stream homework type.
Mission bit stream is static information, and log-on message is multidate information.
For example, a task is arranged, its parameter has 4, is respectively A, B, C, D, and A is integer type, and B is character string type, and C is date type, and D is character string type.This information is mission bit stream.
When starting this task, the value of A is 10, the value of B is "/root/input0 " (the input data position when B represents this tasks carrying), C is current date, the value of D is "/root/output0 " (the output data position when D represents this tasks carrying), this information is log-on message.Log-on message is configuration task and dynamically input when starting each time.
In the present embodiment, carry out the task encapsulation with the C++ program as loading routine.Described C++ program file is called helloworld.cpp, saves as the text formatting file.In standard Linux operating system, adopt the gcc compiler that the helloworld.cpp file is compiled, output executable file helloworld.exe.
Described file helloworld.exe is copied to distributed system, task engine is that described helloworld.exe file is set the parameter that the user needs, described parameter is mission bit stream, the value of described parameter is log-on message, the shell task of distributed file system is when calling helloworld.exe, described helloworld.exe file and mission bit stream are as a task, described shell task is when calling this task, by task engine, log-on message is passed to the shell task, above-mentioned task can be carried out in distributed system.
The present invention encapsulates the program of non-Java language compiling, makes the MapReduce computation model support the program of non-Java language compiling, has satisfied the diversified computation requirement of user; The present invention supports more compute type, when solving practical problems, can more focus on service logic but not to the encapsulation of the bottom of calculation task, solves the actual production demand faster and betterly.Shell task used in the present invention includes the self-defining service logic information of storage address information, log-on message and user program of task, circulation that can control program, thus satisfy the computation requirement of user's complexity.
Embodiment two:
Based on same inventive concept, the present invention also provides a kind of task packaging system based on the MapReduce computation model, comprises that the first judge module, packetization module, first are transmitted module, the second judge module, second transmits module and package module; Wherein,
Described the first judge module is used for obtaining loading routine, judges whether described loading routine is the Java program compiler that the MapReduce computation model is supported;
Described packetization module is used for when described loading routine described input being packaged as the task of Java homework type during with regard to the Java program compiler of MapReduce computation model support, namely uses Java standard packing device that the Java program compiler is packaged into the Jar formatted file;
Described first transmits module, is used for the mission bit stream of described Java homework type is passed to the shell task that the MapReduce computation model moves;
Described the second judge module is used for judging whether described loading routine is the program of stream homework type;
Described second transmits module, is used for the mission bit stream of described stream homework type is passed to the shell task that the MapReduce computation model moves;
Described package module is used for described loading routine is encapsulated as the task of flowing homework type, and the mission bit stream that flows homework type is passed to the MapReduce computation model.
Described the first judge module also comprises the test submodule; Wherein,
Described test submodule is used for the interface standard according to the definition of MapReduce computation model, and described loading routine is tested.
Described package module comprises the transmission submodule; Wherein,
Described transmission submodule is used for the task of described stream homework type is saved in distributed computing system, and the task start information of described stream homework type is passed to described shell task.
Described stream homework type comprises the executable program under the Linux environment.
Executable program under described Linux environment comprises the executable file of Linux shell, Python or perl script program, computer program output after compiling.
The log-on message of the task of described stream homework type comprises the call instruction information of the task of described stream homework type.
Task packaging system based on the MapReduce computation model of the present invention, the present invention encapsulates the program of non-Java language compiling, makes the MapReduce computation model support the program of non-Java language compiling, has satisfied the diversified computation requirement of user; The present invention supports more compute type, when solving practical problems, can more focus on service logic but not to the encapsulation of the bottom of calculation task, solves the actual production demand faster and betterly.Shell task used in the present invention includes the self-defining service logic information of storage address information, log-on message and user program of task, circulation that can control program, thus satisfy the computation requirement of user's complexity.
Obviously, above-described embodiment is only for example clearly is described, and is not the restriction to embodiment.For those of ordinary skill in the field, can also make other changes in different forms on the basis of the above description.Here need not also can't give all embodiments exhaustive.And the apparent variation of being extended out thus or change still are among the protection domain of the invention.
Claims (12)
1. the task method for packing based on the MapReduce computation model, is characterized in that, comprises the steps:
S1, task engine obtains loading routine, judges that whether described loading routine is the Java program compiler that the MapReduce computation model is supported, if, execution in step S2; If not, execution in step S4;
S2 uses Java standard packing device that the Java program compiler is packaged into the Jar formatted file;
S3 passes to the positional information of Jar formatted file the shell task of moving in the MapReduce computation model;
S4 judges whether described loading routine is the program of stream homework type, if, execution in step S5; If not, execution in step S6;
S5, program that will the stream homework type is as the task of stream homework type, and the mission bit stream that will flow homework type passes to the shell task of moving in the MapReduce computation model;
S6 is encapsulated as described loading routine the task of flowing homework type, and the mission bit stream that flows homework type is passed to the shell task of moving in the MapReduce computation model.
2. task method for packing according to claim 1, is characterized in that, in described step S1, judges that whether described task is the Java program compiler that the MapReduce computation model is supported, comprises the steps:
S101 according to the interface standard of MapReduce computation model definition, tests described loading routine, if return to normal data, determines that described loading routine is the Java program compiler that the MapReduce computation model is supported; Otherwise, determine that described task type is not the java applet compiling file that the MapReduce computation model is supported.
3. task method for packing according to claim 1 and 2, is characterized in that, in described step S6, described loading routine is encapsulated as the task of stream homework type, comprises the steps:
S601, described loading routine is saved in distributed computing system, and described loading routine log-on message is passed to described shell task, with described loading routine and the log-on message task as the stream homework type, when described shell task call should be flowed the task of homework type, carry out loading routine by the described log-on message of calling this stream homework type task.
4. according to claim 1-3 arbitrary described task method for packing, is characterized in that, described stream homework type comprises the executable program under the Linux environment.
5. task method for packing according to claim 4, is characterized in that, the executable program under described Linux environment comprises the executable file of Linux shell, Python or Per l shell script, computer program output after compiling.
6. task method for packing according to claim 3, is characterized in that, the log-on message of the task of described stream homework type comprises the call instruction information of the task of described stream homework type.
7. the task packaging system based on the MapReduce computation model, is characterized in that, comprises that the first judge module, packetization module, first are transmitted module, the second judge module, second transmits module and package module;
Wherein,
Described the first judge module is used for obtaining loading routine, judges whether described loading routine is the Java program compiler that the MapReduce computation model is supported;
Described packetization module is used for described input being packaged as the task of Java homework type when described loading routine is the Java program compiler of MapReduce computation model support, namely uses Java standard packing device that the Java program compiler is packaged into the Jar formatted file;
Described first transmits module, is used for the mission bit stream of described Java homework type is passed to the shell task that the MapReduce computation model moves;
Described the second judge module is used for judging whether described loading routine is the program of stream homework type;
Described second transmits module, is used for the mission bit stream of described stream homework type is passed to the shell task that the MapReduce computation model moves;
Described package module is used for described loading routine is encapsulated as the task of flowing homework type, and the mission bit stream that flows homework type is passed to the MapReduce computation model.
8. task packaging system according to claim 7, is characterized in that, described the first judge module comprises the test submodule;
Wherein,
Described test submodule is used for the interface standard according to the definition of MapReduce computation model, and described loading routine is tested.
9. according to claim 7 or 8 described task packaging systems, is characterized in that described package module comprises the transmission submodule;
Wherein,
Described transmission submodule is used for the task of described stream homework type is saved in distributed computing system, and the task start information of described stream homework type is passed to described shell task.
10. according to claim 7-9 arbitrary described task packaging systems, is characterized in that, described stream homework type comprises the executable program under the Linux environment.
11. task packaging system according to claim 10 is characterized in that, the executable program under described Linux environment comprises the executable file of Linux shell, Python or Per l shell script, computer program output after compiling.
12. task packaging system according to claim 9 is characterized in that, the log-on message of the task of described stream homework type comprises the call instruction information of the task of described stream homework type.
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