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Releases: cylondata/twister2

Twister2 Release 0.2.2

14 Jun 19:30
@chathurawidanage chathurawidanage
0.2.2
885a631
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Twister2 Release 0.2.2

Twister2 Release 0.2.2

This is a patch release of Twister2 with first versions of few major features.

You can download source code from Github

First version of major features

  1. Streaming windowing support
  2. Join operations included in Task API
  3. Run OpenMPI programs inside task graph
  4. Checkpointing for streaming and batch applications

Minor features

Apart from these, we have done API refactorings and many improvements to performance

Next Release

We are working on to consolidate the features introduced in this release. Also we are continuing to
improve the code, fix bugs etc.

Components in Twister2

We support the following components in Twister2

  1. Resource provisioning component to bring up and manage parallel workers in cluster environments
    1. Standalone
    2. Kubernetes
    3. Mesos
    4. Slurm
    5. Nomad
  2. Parallel and Distributed Operators in HPC and Cloud Environments
    1. Twister2:Net - a data level dataflow operator library for streaming and large scale batch analysis
    2. Harp - a BSP (Bulk Synchronous Processing) innovative collective framework for parallel applications and machine learning at message level
    3. OpenMPI (HPC Environments only) at message level
  3. Task System
    1. Task Graph
      • Create dataflow graphs for streaming and batch analysis including iterative computations
    2. Task Scheduler - Schedule the task graph into cluster resources supporting different scheduling algorithms
      • Datalocality Scheduling
      • Roundrobin scheduling
      • First fit scheduling
    3. Executor - Execution of task graph
      • Batch executor
      • Streaming executor
  4. TSet for distributed data representation (Similar to Spark RDD, Flink DataSet and Heron Streamlet)
    1. Iterative computations
    2. Data caching
  5. APIs for streaming and batch applications
    1. Operator API
    2. Task Graph based API
    3. TSet API
  6. Support for storage systems
    1. HDFS
    2. Local file systems
    3. NFS for persistent storage
  7. Web UI for monitoring Twister2 Jobs
  8. Apache Storm Compatibility API
  9. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
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Twister2 Release 0.2.1

10 May 18:14
@chathurawidanage chathurawidanage
0.2.1
7b308a2
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Twister2 Release 0.2.1

Twister2 Release 0.2.1

Twister2 0.2.1 is a patch release of Twister2 where we improve its performance and bugs.

We have add Streaming windowing support as a new beta feature to this release.

You can download source code from Github

Major Features

This release includes the core components of realizing the above goals.

  1. Resource provisioning component to bring up and manage parallel workers in cluster environments
    1. Standalone
    2. Kubernetes
    3. Mesos
    4. Slurm
    5. Nomad
  2. Parallel and Distributed Operators in HPC and Cloud Environments
    1. Twister2:Net - a data level dataflow operator library for streaming and large scale batch analysis
    2. Harp - a BSP (Bulk Synchronous Processing) innovative collective framework for parallel applications and machine learning at message level
    3. OpenMPI (HPC Environments only) at message level
  3. Task System
    1. Task Graph
      • Create dataflow graphs for streaming and batch analysis including iterative computations
    2. Task Scheduler - Schedule the task graph into cluster resources supporting different scheduling algorithms
      • Datalocality Scheduling
      • Roundrobin scheduling
      • First fit scheduling
    3. Executor - Execution of task graph
      • Batch executor
      • Streaming executor
  4. TSet for distributed data representation (Similar to Spark RDD, Flink DataSet and Heron Streamlet)
    1. Iterative computations
    2. Data caching
  5. APIs for streaming and batch applications
    1. Operator API
    2. Task Graph based API
    3. TSet API
  6. Support for storage systems
    1. HDFS
    2. Local file systems
    3. NFS for persistent storage
  7. Web UI for monitoring Twister2 Jobs
  8. Apache Storm Compatibility API
  9. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job

These features translates to running following types of applications natively with high performance.

  1. Streaming computations
  2. Data operations in batch mode
  3. Iterative computations

Examples

With this release we include several examples to demonstrate various features of Twister2.

  1. A Hello World example
  2. Communication examples - how to use communications for streaming and batch
  3. Task examples - how to create task graphs with different operators for streaming and batch
  4. K-Means
  5. Sorting of records
  6. Word count
  7. Iterative examples
  8. Harp example
  9. SVM

Road map

We have started working on our next major release that will connect the core components we have developed
into a full data analytics environment. In particular it will focus on providing APIs around the core
capabilities of Twister2 and integration of applications in a single dataflow.

Next Major Release (End of June 2019)

  1. Connected DataFlow
  2. Fault tolerance
  3. Supporting more API's including Beam
  4. More example applications

Beyond next release

  1. Python API
  2. Implementing core parts of Twister2 with C/C++ for high performance
  3. Direct use of RDMA
  4. SQL interface
  5. Native MPI support for cloud deployments
  6. More resource managers - Pilot Jobs, Yarn

License

Licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0

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Twister2 Release 0.2.0

28 Mar 20:54
@chathurawidanage chathurawidanage
v0.2.0
506bde4
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Twister2 Release 0.2.0

Twister2 Release 0.2.0

Twister2 0.2.0 is the second open source public release of Twister2. We are excited to bring another release of our
high performance data analytics hosting environment that can work in both cloud and HPC environments.

You can download source code from Github

Major Features

This release includes the core components of realizing the above goals.

  1. Resource provisioning component to bring up and manage parallel workers in cluster environments
    1. Standalone
    2. Kubernetes
    3. Mesos
    4. Slurm
    5. Nomad
  2. Parallel and Distributed Communications in HPC and Cloud Environments
    1. Twister2:Net - a data level dataflow communication library for streaming and large scale batch analysis
    2. Harp - a BSP (Bulk Synchronous Processing) innovative collective framework for parallel applications and machine learning at message level
    3. OpenMPI (HPC Environments only) at message level
  3. Task System
    1. Task Graph
      • Create dataflow graphs for streaming and batch analysis including iterative computations
    2. Task Scheduler - Schedule the task graph into cluster resources supporting different scheduling algorithms
      • Datalocality Scheduling
      • Roundrobin scheduling
      • First fit scheduling
    3. Executor - Execution of task graph
      • Batch executor
      • Streaming executor
  4. API for creating Task Graph and Communication
    1. Communication API
    2. Task based API
    3. Data API (TSet API)
  5. Support for storage systems
    1. HDFS
    2. Local file systems
    3. NFS for persistent storage
  6. Web UI for monitoring Twister2 Jobs
  7. Apache Storm Compatibility API

These features translates to running following types of applications natively with high performance.

  1. Streaming computations
  2. Data operations in batch mode
  3. Iterative computations

Examples

With this release we include several examples to demonstrate various features of Twister2.

  1. A Hello World example
  2. Communication examples - how to use communications for streaming and batch
  3. Task examples - how to create task graphs with different operators for streaming and batch
  4. K-Means
  5. Sorting of records
  6. Word count
  7. Iterative examples
  8. Harp example
  9. SVM

Road map

We have started working on our next major release that will connect the core components we have developed
into a full data analytics environment. In particular it will focus on providing APIs around the core
capabilities of Twister2 and integration of applications in a single dataflow.

Next Major Release (End of June 2019)

  1. Connected DataFlow
  2. Fault tolerance
  3. Supporting more API's including Beam
  4. Python API
  5. More resource managers - Pilot Jobs, Yarn
  6. More example applications

Beyond next release

  1. Implementing core parts of Twister2 with C/C++ for high performance
  2. Direct use of RDMA
  3. SQL interface
  4. Native MPI support for cloud deployments

License

Licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0

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Twister2 v0.1.0

05 Oct 20:30
@chathurawidanage chathurawidanage
v0.1.0
9cddbee
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Twister2 v0.1.0 Pre-release
Pre-release

Twister2 Release 0.1.0

Twister2 0.1.0 is the first open source public release of Twister2. We are excited to bring a high performance data analytics
hosting environment that can work in both cloud and HPC environments. This is the first step towards
building a complete end to end high performance solution for data analytics ranging from streaming to batch analysis to
machine learning applications. Our vision is to make the system work seamlessly both in cloud and HPC environments ranging from single machines to large clusters.

You can download source code from Github

Major Features

This release includes the core components of realizing the above goals.

  1. Resource provisioning component to bring up and manage parallel workers in cluster environments
    1. Standalone
    2. Kubernetes
    3. Mesos
    4. Slurm
    5. Nomad
  2. Parallel and Distributed Communications in HPC and Cloud Environments
    1. Twister2:Net - a data level dataflow communication library for streaming and large scale batch analysis
    2. Harp - a BSP (Bulk Synchronous Processing) innovative collective framework for parallel applications and machine learning at message level
    3. OpenMPI (HPC Environments only) at message level
  3. Task Graph - Create dataflow graphs for streaming and batch analysis including iterative computations
  4. Task Scheduler - Schedule the task graph into cluster resources supporting different scheduling algorithms
    1. Datalocality Scheduling
    2. Roundrobin scheduling
    3. First fit scheduling
  5. Executor - Execution of task graph
    1. Batch executor
    2. Streaming executor
  6. API for creating Task Graph and Communication
    1. Communication API
    2. Task based API
  7. Support for storage systems
    1. HDFS
    2. Local file systems
    3. NFS for persistent storage

These features translates to running following types of applications natively with high performance.

  1. Streaming computations
  2. Data operations in batch mode
  3. Iterative computations

Examples

With this release we include several examples to demonstrate various features of Twister2.

  1. A Hello World example
  2. Communication examples - how to use communications for streaming and batch
  3. Task examples - how to create task graphs with different operators for streaming and batch
  4. K-Means
  5. Sorting of records
  6. Word count
  7. Iterative examples
  8. Harp example

Road map

We have started working on our next major release that will connect the core components we have developed
into a full data analytics environment. In particular it will focus on providing APIs around the core
capabilities of Twister2 and integration of applications in a single dataflow.

Next release (End of December 2018)

  1. Hierarchical task scheduling - Ability to run different types of jobs in a single dataflow
  2. Fault tolerance
  3. Data API including DataSet similar to Spark RDD, Flink DataSet and Heron Streamlet
  4. Supporting different API's including Storm, Spark, Beam
  5. Heterogeneous resources allocations
  6. Web UI for monitoring Twister2 Jobs
  7. More resource managers - Pilot Jobs, Yarn
  8. More example applications

Beyond next release

  1. Implementing core parts of Twister2 with C/C++ for high performance
  2. Python APIs
  3. Direct use of RDMA
  4. FaaS APIs
  5. SQL interface
  6. Native MPI support for cloud deployements

License

Licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0

Assets 2
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