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private void myMethod () {Dictionary d =
new Hashtable()
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}
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, 0, outputIndex); return Optional.of(new DefaultCardinalityEstimator(1d, 1, this.isSupportingBroadcastInputs(), inputCards -> inputCards[0])); }
long[] lowerAndUpperInputEstimates = this.extractEstimateValues(inputEstimates);
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, 0, outputIndex); return Optional.of(new DefaultCardinalityEstimator(1d, 1, this.isSupportingBroadcastInputs(), inputCards -> inputCards[0])); }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, 0, outputIndex); return Optional.of(new DefaultCardinalityEstimator(1d, 1, this.isSupportingBroadcastInputs(), inputCards -> inputCards[0])); }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); return Optional.of(new DefaultCardinalityEstimator(1d, 2, this.isSupportingBroadcastInputs(), inputCards -> inputCards[0] + inputCards[1])); }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); return Optional.of(new DefaultCardinalityEstimator( 1d, 1, this.isSupportingBroadcastInputs(), inputCards -> inputCards[0] )); } }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); // The current idea: We assume, we have a foreign-key like join // TODO: Find a better estimator. return Optional.of(new DefaultCardinalityEstimator( .5d, 2, this.isSupportingBroadcastInputs(), inputCards -> 3 * Math.max(inputCards[0], inputCards[1]) )); } }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); // The current idea: We assume that one side is duplicate-free and included in the other. // TODO: Find a better estimator. return Optional.of(new DefaultCardinalityEstimator( .5d, 2, this.isSupportingBroadcastInputs(), inputCards -> Math.min(inputCards[0], inputCards[1]) )); } }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); // TODO: Come up with a dynamic estimator. // Assume with a confidence of 0.7 that 70% of the data quanta are pairwise distinct. return Optional.of(new DefaultCardinalityEstimator(0.7d, 1, this.isSupportingBroadcastInputs(), inputCards -> (long) (inputCards[0] * 0.7d))); } }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); // TODO: Come up with a decent way to estimate the "distinctness" of reduction keys. return Optional.of(new DefaultCardinalityEstimator( 0.5d, 1, this.isSupportingBroadcastInputs(), inputCards -> (long) (inputCards[0] * 0.1))); } }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); // TODO: Come up with a decent way to estimate the "distinctness" of reduction keys. return Optional.of(new DefaultCardinalityEstimator(0.5d, 1, this.isSupportingBroadcastInputs(), inputCards -> (long) (inputCards[0] * 0.1))); }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); return Optional.of(new DefaultCardinalityEstimator( 1d, 2, this.isSupportingBroadcastInputs(), inputCards -> inputCards[0] * inputCards[1] )); } }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); return Optional.of(new DefaultCardinalityEstimator(1d, 1, this.isSupportingBroadcastInputs(), inputCards -> inputCards[0])); }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); return Optional.of(new DefaultCardinalityEstimator(1d, 1, this.isSupportingBroadcastInputs(), inputCards -> inputCards[0])); } }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); // The current idea: We assume, we have a foreign-key like join // TODO: Find a better estimator. return Optional.of(new DefaultCardinalityEstimator( .5d, 2, this.isSupportingBroadcastInputs(), inputCards -> (long) (0.1 * (inputCards[0] + inputCards[1])) )); } }
@Override public Optional<CardinalityEstimator> createCardinalityEstimator( final int outputIndex, final Configuration configuration) { Validate.inclusiveBetween(0, this.getNumOutputs() - 1, outputIndex); return Optional.of(new DefaultCardinalityEstimator(1d, this.getNumInputs(), this.isSupportingBroadcastInputs(), inputCards -> this.collection.size())); }
vertexDistincter.at(epoch); vertexDistincter.setName(String.format("%s (distinct vertices)", operatorBaseName)); vertexDistincter.setCardinalityEstimator(0, new DefaultCardinalityEstimator( 0.5d, 1, false, longs -> Math.round(longs[0] * NUM_VERTICES_PER_EDGE / 2) )); adjacencyCreator.at(epoch); adjacencyCreator.setName(String.format("%s (create adjacencies)", operatorBaseName)); adjacencyCreator.setCardinalityEstimator(0, new DefaultCardinalityEstimator( 0.5d, 1, false, longs -> Math.round(longs[0] * NUM_VERTICES_PER_EDGE) )); rankJoin.at(epoch); rankJoin.setName(String.format("%s (join adjacencies and ranks)", operatorBaseName)); rankJoin.setCardinalityEstimator(0, new DefaultCardinalityEstimator( .99d, 2, false, longs -> longs[0] )); sumPartialRanks.at(epoch); sumPartialRanks.setName(String.format("%s (sum partial ranks)", operatorBaseName)); sumPartialRanks.setCardinalityEstimator(0, new DefaultCardinalityEstimator( 0.5d, 1, false, longs -> Math.round(longs[0] * NUM_VERTICES_PER_EDGE) ));