Abstract: A computer-implemented method comprises obtaining a first build task for building first source code in a first programming language of a plurality of programming languages; retrieving, by the processor, the first source code based on the first build task; building the first source code into one or more artifacts and one or more job specifications; storing the one or more artifacts in a cache shared across a cluster; and initializing an application module on the cluster based on the first programming language, the application module configured to receive a job specification of the one or more job specifications and execute a data transformation job using a reference to a location in the cache.

Abstract: Data transformation in a distributed system of applications and data repositories is described. The subsystems for the overall framework are distributed, thereby allowing for customization to require only isolated changes to one or more subsystems. In one embodiment, a source code repository is used to receive and store source code. A build subsystem can retrieve source code from the source code repository and build it, using one or more criteria. By building the source code, the build subsystem can generate an artifact, which is executable code, such as a JAR or SQL file. Likewise, by building the source code, the build subsystem can generate one or more job specifications for executing the executable code. In one embodiment, the artifact and job specification may be used to launch an application server in a cluster. The application server can then receive data transformation instructions and execute the data transformation instructions.

Abstract: Systems, methods, and non-transitory computer readable media are provided for managing expiration of modules. An expiry dataset may be maintained. The expiry dataset may include a set of identifiers corresponding to a set of modules, a set of expiry values for the set of modules, and a set of termination tasks for the set of modules. A request to refresh a module may be received from a client. Responsive to the reception of the request, an expiry value and a termination task for the module within the expiry dataset may be updated. The expiry value may be independent of a timestamp associated with the request.

Abstract: Systems, methods, and non-transitory computer readable media are provided for managing expiration of modules. An expiry dataset may be maintained. The expiry dataset may include a set of identifiers corresponding to a set of modules, a set of expiry values for the set of modules, and a set of termination tasks for the set of modules. A request to refresh a module may be received from a client. Responsive to the reception of the request, an expiry value and a termination task for the module within the expiry dataset may be updated. The expiry value may be independent of a timestamp associated with the request.

Abstract: Data transformation in a distributed system of applications and data repositories is described. The subsystems for the overall framework are distributed, thereby allowing for customization to require only isolated changes to one or more subsystems. In one embodiment, a source code repository is used to receive and store source code. A build subsystem can retrieve source code from the source code repository and build it, using one or more criteria. By building the source code, the build subsystem can generate an artifact, which is executable code, such as a JAR or SQL file. Likewise, by building the source code, the build subsystem can generate one or more job specifications for executing the executable code. In one embodiment, the artifact and job specification may be used to launch an application server in a cluster. The application server can then receive data transformation instructions and execute the data transformation instructions.

Abstract: Systems, methods, and non-transitory computer readable media are provided for managing expiration of modules. An expiry dataset may be maintained. The expiry dataset may include a set of identifiers corresponding to a set of modules, a set of expiry values for the set of modules, and a set of termination tasks for the set of modules. A request to refresh a module may be received from a client. Responsive to the reception of the request, an expiry value and a termination task for the module within the expiry dataset may be updated. The expiry value may be independent of a timestamp associated with the request.

Abstract: Systems, methods, and non-transitory computer readable media are provided for managing assignment of modules. A job from a client may be received. The job may be inserted into a job queue. The job within the job queue may be compared with a set of cooldown modules to determine whether a compatible cooldown module is available. The job may be assigned to the compatible cooldown module responsive to the compatible cooldown module being available.

Abstract: Systems, methods, and non-transitory computer readable media are provided for managing assignment of modules. A job from a client may be received. The job may be inserted into a job queue. The job within the job queue may be compared with a set of cooldown modules to determine whether a compatible cooldown module is available. The job may be assigned to the compatible cooldown module responsive to the compatible cooldown module being available.

Abstract: Data transformation in a distributed system of applications and data repositories is described. The subsystems for the overall framework are distributed, thereby allowing for customization to require only isolated changes to one or more subsystems. In one embodiment, a source code repository is used to receive and store source code. A build subsystem can retrieve source code from the source code repository and build it, using one or more criteria. By building the source code, the build subsystem can generate an artifact, which is executable code, such as a JAR or SQL file. Likewise, by building the source code, the build subsystem can generate one or more job specifications for executing the executable code. In one embodiment, the artifact and job specification may be used to launch an application server in a cluster. The application server can then receive data transformation instructions and execute the data transformation instructions.

Abstract: Data transformation in a distributed system of applications and data repositories is described. The subsystems for the overall framework are distributed, thereby allowing for customization to require only isolated changes to one or more subsystems. In one embodiment, a source code repository is used to receive and store source code. A build subsystem can retrieve source code from the source code repository and build it, using one or more criteria. By building the source code, the build subsystem can generate an artifact, which is executable code, such as a JAR or SQL file. Likewise, by building the source code, the build subsystem can generate one or more job specifications for executing the executable code. In one embodiment, the artifact and job specification may be used to launch an application server in a cluster. The application server can then receive data transformation instructions and execute the data transformation instructions.

Abstract: Data transformation in a distributed system of applications and data repositories is described. The subsystems for the overall framework are distributed, thereby allowing for customization to require only isolated changes to one or more subsystems. In one embodiment, a source code repository is used to receive and store source code. A build subsystem can retrieve source code from the source code repository and build it, using one or more criteria. By building the source code, the build subsystem can generate an artifact, which is executable code, such as a JAR or SQL file. Likewise, by building the source code, the build subsystem can generate one or more job specifications for executing the executable code. In one embodiment, the artifact and job specification may be used to launch an application server in a cluster. The application server can then receive data transformation instructions and execute the data transformation instructions.