| BalanceToAvgFederatedScheme |
Balance to Avg Federated scheme
When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
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| DataPartitionerSparkAggregator |
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| DataPartitionerSparkMapper |
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| DataPartitionFederatedScheme |
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| DataPartitionFederatedScheme.BalanceMetrics |
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| DataPartitionFederatedScheme.Result |
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| DataPartitionLocalScheme |
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| DataPartitionSparkScheme |
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| DCLocalScheme |
Disjoint_Contiguous data partitioner:
for each worker, use a right indexing
operation X[beg:end,] to obtain contiguous,
non-overlapping partitions of rows.
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| DCSparkScheme |
Spark Disjoint_Contiguous data partitioner:
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| DRLocalScheme |
Data partitioner Disjoint_Random:
for each worker, use a permutation multiply P[beg:end,] %*% X,
where P is constructed for example with P=table(seq(1,nrow(X)),sample(nrow(X), nrow(X))),
i.e., sampling without replacement to ensure disjointness.
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| DRRLocalScheme |
Disjoint_Round_Robin data partitioner:
for each worker, use a permutation multiply
or simpler a removeEmpty such as removeEmpty
(target=X, margin=rows, select=(seq(1,nrow(X))%%k)==id)
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| DRRSparkScheme |
Spark Disjoint_Round_Robin data partitioner:
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| DRSparkScheme |
Spark data partitioner Disjoint_Random:
For the current row block, find all the shifted place for each row (WorkerID => (row block ID, matrix)
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| FederatedDataPartitioner |
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| KeepDataOnWorkerFederatedScheme |
Keep Data on Worker Federated scheme
When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
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| LocalDataPartitioner |
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| ORLocalScheme |
Data partitioner Overlap_Reshuffle:
for each worker, use a new permutation multiply P %*% X,
where P is constructed for example with P=table(seq(1,nrow(X),sample(nrow(X), nrow(X))))
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| ORSparkScheme |
Spark data partitioner Overlap_Reshuffle:
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| ReplicateToMaxFederatedScheme |
Replicate to Max Federated scheme
When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
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| ShuffleFederatedScheme |
Shuffle Federated scheme
When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
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| SparkDataPartitioner |
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| SubsampleToMinFederatedScheme |
Subsample to Min Federated scheme
When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
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