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Releases: cylondata/twister2

Twister2 Release 0.8.0

02 Oct 22:49
@chathurawidanage chathurawidanage
0.8.0
bb1de35
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Twister2 Release 0.8.0 Latest
Latest

Twister2 Release 0.8.0

This is a major release of Twister2.

You can download source code from Github

Features of this release

  1. Fault Tolerance enhancements
  2. Apache Beam integration is now official Beam Docs
  3. Improvements to configurations
  4. Major TSet API update

Minor features

Apart from these, we have done many code improvements and bug fixes.

Next Release

In the next release we are working to,

  • Improve and release Table API
  • TSQL; Adding SQL support

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. Apache BEAM API
  10. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
Assets 2
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Twister2 Release 0.7.0

17 Jul 21:55
@chathurawidanage chathurawidanage
0.7.0
259fd7e
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Twister2 Release 0.7.0

This is a major release of Twister2.

You can download source code from Github

Features of this release

  1. Fault Tolerance enhancements; Automated fault detection and recovery
  2. Table API(experimental)
  3. TSet API improvements; Pipe capability and TSetEnvironement

Minor features

Apart from this, we have done many code improvements and bug fixes.

Next Release

In the next release, we are working to,

  • Improve and release Table API
  • TSQL; Adding SQL support

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. Apache BEAM API
  10. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
Assets 2
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Twister2 Release 0.6.0

17 Feb 19:01
@pulasthi pulasthi
0.6.0
6b8373f
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Twister2 Release 0.6.0

This is a major release of Twister2.

You can download source code from Github

Features of this release

  1. Adds support required for the Twister2 Beam runner

Minor features

Apart from this, we have done many code improvements and bug fixes.

Next Release

In the next release, we are working to improve the Fault tolerance, fix issues and integrate with AI
systems.

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. Apache BEAM API
  10. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
Assets 2
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Twister2 Release 0.5.0

08 Feb 14:55
@chathurawidanage chathurawidanage
0.5.0
e8755f7
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Twister2 Release 0.5.0

This is a major release of Twister2.

You can download source code from Github

Features of this release

  1. Support for UCX
  2. Performance improvements of shuffle operations
  3. Hash Join implementation
  4. Windowing support for TSet API
  5. CSV data readers

Minor features

Apart from these, we have done many code improvements and bug fixes.

Next Release

In the next release we are working to improve the Fault tolerance, fix issues and integrate with AI
systems.

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. Apache BEAM API
  10. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
Assets 2
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Twister2 Release 0.5.0 RC1

04 Feb 19:41
@chathurawidanage chathurawidanage
0.5.0-rc1
e8755f7
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Twister2 Release 0.5.0 RC1 Pre-release
Pre-release

This is a pre-release release of Twister2.

You can download source code from Github

Features of this release

  1. Support for UCX
  2. Performance improvements of shuffle operations
  3. Hash Join implementation
  4. Windowing support for TSet API
  5. CSV data readers

Minor features

Apart from these, we have done many code improvements and bug fixes.

Next Release

In the next release we are working to improve the Fault tolerance, fix issues and integrate with AI
systems.

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. Apache BEAM API
  10. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
Assets 2
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Twister2 Release 0.4.0

03 Dec 20:18
@chathurawidanage chathurawidanage
0.4.0
c904179
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
Expired
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Twister2 Release 0.4.0

This is a major release of Twister2.

You can download source code from Github

Features of this release

In this release we moved to OpenMPI 4.0.1 and Python 3. Also we tested Twister2 with JDK 11.

  1. Python API
  2. Fully functioning TSet API
  3. ZooKeeper based automatic restart of workers when failures happen
  4. Improvements to performance including a new routing algorithm for shuffle operations
  5. BEAM integration improvements

Minor features

Apart from these, we have done many code improvements and bug fixes.

Next Release

In the next release we are working to improve the Fault tolerance, fix issues and integrate with AI
systems.

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. Apache BEAM API
  10. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
Assets 2
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Twister2 Release 0.4.0 RC1

27 Nov 21:28
@chathurawidanage chathurawidanage
0.4.0-rc1
90a7c60
Compare
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Twister2 Release 0.4.0 RC1 Pre-release
Pre-release

Twister2 Release 0.4.0

This is a major release of Twister2.

You can download source code from Github

Features of this release

In this release we moved to OpenMPI 4.0.1 and Python 3. Also we tested Twister2 with JDK 11.

  1. Python API
  2. Fully functioning TSet API
  3. ZooKeeper based automatic restart of workers when failures happen
  4. Improvements to performance including a new routing algorithm for shuffle operations
  5. BEAM integration improvements

Minor features

Apart from these, we have done many code improvements and bug fixes.

Next Release

In the next release we are working onto consolidate the Apache Beam integration and improve the
fault tolerance (automatic restart of wokers)

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. Apache BEAM API
  10. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
Assets 2
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Twister2 Release 0.3.0

06 Sep 19:27
@pulasthi pulasthi
0.3.0
a74e185
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
Expired
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Compare
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Twister2 Release 0.3.0

This is a major release of Twister2.

You can download source code from Github

Features of this release

In this release we moved to OpenMPI 4.0.1 and Python 3. Also we tested Twister2 with JDK 11.

  1. The initial version of Apache BEAM integration
  2. Fully functioning TSet API
  3. Simulator for writing applications with IDE
  4. Organize the APIs to facilitate easy creation of applications
  5. Improvements to performance including a new routing algorithm for shuffle operations
  6. Improved batch task scheduler (new batch scheduler)
  7. Inner joins and outer joins
  8. Support for reading HDFS files through TSet API
  9. The initial version of fault tolerance with manual restart
  10. Configuration structure improvements
  11. Nomad scheduler improvements
  12. New documentation website

Minor features

Apart from these, we have done many code improvements and bug fixes.

Next Release

In the next release we are working onto consolidate the Apache Beam integration and improve the
fault tolerance (automatic restart of wokers)

Assets 2
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Twister2 Release 0.3.0-rc2

29 Aug 20:07
@chathurawidanage chathurawidanage
0.3.0-rc2
87c6c66
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Twister2 Release 0.3.0-rc2 Pre-release
Pre-release

This is a major release of Twister2.

You can download source code from Github

Features of this release

In this release we moved to OpenMPI 4.0.1 and Python 3. Also we tested Twister2 with JDK 11.

  1. The initial version of Apache BEAM integration
  2. Fully functioning TSet API
  3. Simulator for writing applications with IDE
  4. Organize the APIs to facilitate easy creation of applications
  5. Improvements to performance including a new routing algorithm for shuffle operations
  6. Improved batch task scheduler (new batch scheduler)
  7. Inner joins and outer joins
  8. Support for reading HDFS files through TSet API
  9. The initial version of fault tolerance with manual restart
  10. Configuration structure improvements
  11. Nomad scheduler improvements
  12. New documentation website

Minor features

Apart from these, we have done many code improvements and bug fixes.

Next Release

In the next release we are working onto consolidate the Apache Beam integration and improve the
fault tolerance (automatic restart of wokers)

Assets 2
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0.3.0-rc1

24 Aug 04:07
@pulasthi pulasthi
0.3.0-rc1
e4b2d09
Compare
Choose a tag to compare
0.3.0-rc1 Pre-release
Pre-release

Twister2 Release 0.3.0-rc1

This is a major release of Twister2.

You can download source code from Github

Features of this release

In this release we moved to OpenMPI 4.0.1 and Python 3. Also we tested Twister2 with JDK 11.

  1. The initial version of Apache BEAM integration
  2. Fully functioning TSet API
  3. Simulator for writing applications with IDE
  4. Organize the APIs to facilitate easy creation of applications
  5. Improvements to performance including a new routing algorithm for shuffle operations
  6. Improved batch task scheduler (new batch scheduler)
  7. Inner joins and outer joins
  8. Support for reading HDFS files through TSet API
  9. The initial version of fault tolerance with manual restart
  10. Configuration structure improvements
  11. Nomad scheduler improvements
  12. New documentation website

Minor features

Apart from these, we have done many code improvements and bug fixes.

Next Release

In the next release we are working onto consolidate the Apache Beam integration and improve the
fault tolerance (automatic restart of wokers)

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. Apache BEAM API
  10. Connected DataFlow (Experimental)
    1. Supports creation of multiple dataflow graphs executing in a single job
Assets 2
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