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Added a sampling module, currently containing only weighted_sample().
Jira: MADLIB-584 Sampling module: - Added a data-parallel UDA for weighted sampling of a single row C++ AL: - Added a boost/TR1-style front-end to PostgreSQL's random number generator.
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Florian Schoppmann
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Florian Schoppmann
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Jul 19, 2012
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,9 @@ | ||
| /* ----------------------------------------------------------------------------- | ||
| * | ||
| * @file sample.hpp | ||
| * | ||
| * @brief Umbrella header that includes all sampling headers | ||
| * | ||
| * -------------------------------------------------------------------------- */ | ||
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| #include "weighted_sample.hpp" |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,115 @@ | ||
| /* ----------------------------------------------------------------------- *//** | ||
| * | ||
| * @file weighted_sample.cpp | ||
| * | ||
| * @brief Generate a single weighted random sample | ||
| * | ||
| *//* ----------------------------------------------------------------------- */ | ||
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| #include <dbconnector/dbconnector.hpp> | ||
| #include <modules/shared/HandleTraits.hpp> | ||
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| #include <boost/tr1/random.hpp> | ||
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| #include "weighted_sample.hpp" | ||
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| // Import TR1 names (currently used from boost). This can go away once we make | ||
| // the switch to C++11. | ||
| namespace std { | ||
| using tr1::bernoulli_distribution; | ||
| } | ||
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| namespace madlib { | ||
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| namespace modules { | ||
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| namespace sample { | ||
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| /** | ||
| * @brief Transition state for weighted sample | ||
| * | ||
| * Note: We assume that the DOUBLE PRECISION array is initialized by the | ||
| * database with length 2, and all elemenets are 0. | ||
| */ | ||
| template <class Handle> | ||
| class WeightedSampleTransitionState { | ||
| public: | ||
| WeightedSampleTransitionState(const AnyType &inArray) | ||
| : mStorage(inArray.getAs<Handle>()), | ||
| sample_id(&mStorage[1]), | ||
| weight_sum(&mStorage[0]) { } | ||
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| inline operator AnyType() const { | ||
| return mStorage; | ||
| } | ||
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| private: | ||
| Handle mStorage; | ||
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| public: | ||
| typename HandleTraits<Handle>::ReferenceToInt64 sample_id; | ||
| typename HandleTraits<Handle>::ReferenceToDouble weight_sum; | ||
| }; | ||
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| /** | ||
| * @brief Perform the weighted-sample transition step | ||
| */ | ||
| AnyType | ||
| weighted_sample_transition::run(AnyType& args) { | ||
| WeightedSampleTransitionState<MutableArrayHandle<double> > state = args[0]; | ||
| uint64_t identifier = args[1].getAs<int64_t>(); | ||
| double weight = args[2].getAs<double>(); | ||
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| // Instead of throwing an error, we will just ignore rows with a negative | ||
| // weight | ||
| if (weight > 0.) { | ||
| state.weight_sum += weight; | ||
| std::bernoulli_distribution success(weight / state.weight_sum); | ||
| // Note that a NativeRandomNumberGenerator object is stateless, so it | ||
| // is not a problem to instantiate an object for each RN generation... | ||
| NativeRandomNumberGenerator generator; | ||
| if (success(generator)) | ||
| state.sample_id = identifier; | ||
| } | ||
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| return state; | ||
| } | ||
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| /** | ||
| * @brief Perform the merging of two transition states | ||
| */ | ||
| AnyType | ||
| weighted_sample_merge::run(AnyType &args) { | ||
| WeightedSampleTransitionState<MutableArrayHandle<double> > stateLeft | ||
| = args[0]; | ||
| WeightedSampleTransitionState<ArrayHandle<double> > stateRight = args[1]; | ||
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| // FIXME: Once we have more modular states (independent of transition/merge | ||
| // function), implement using the logic from the transition function | ||
| stateLeft.weight_sum += stateRight.weight_sum; | ||
| std::bernoulli_distribution success( | ||
| stateRight.weight_sum / stateLeft.weight_sum); | ||
| // Note that a NativeRandomNumberGenerator object is stateless, so it | ||
| // is not a problem to instantiate an object for each RN generation... | ||
| NativeRandomNumberGenerator generator; | ||
| if (success(generator)) | ||
| stateLeft.sample_id = stateRight.sample_id; | ||
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| return stateLeft; | ||
| } | ||
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| /** | ||
| * @brief Perform the weighted-sample final step | ||
| */ | ||
| AnyType | ||
| weighted_sample_final::run(AnyType &args) { | ||
| WeightedSampleTransitionState<ArrayHandle<double> > state = args[0]; | ||
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| return static_cast<int64_t>(state.sample_id); | ||
| } | ||
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| } // namespace stats | ||
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| } // namespace modules | ||
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| } // namespace madlib |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,20 @@ | ||
| /* ----------------------------------------------------------------------- *//** | ||
| * | ||
| * @file weighted_sample.hpp | ||
| * | ||
| *//* ----------------------------------------------------------------------- */ | ||
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| /** | ||
| * @brief Weighted random sample: Transition function | ||
| */ | ||
| DECLARE_UDF(sample, weighted_sample_transition) | ||
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| /** | ||
| * @brief Weighted random sample: State merge function | ||
| */ | ||
| DECLARE_UDF(sample, weighted_sample_merge) | ||
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| /** | ||
| * @brief Weighted random sample: Final function | ||
| */ | ||
| DECLARE_UDF(sample, weighted_sample_final) |
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72 changes: 72 additions & 0 deletions
72
src/ports/postgres/dbconnector/NativeRandomNumberGenerator_impl.hpp
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| Original file line number | Diff line number | Diff line change |
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| /* ----------------------------------------------------------------------- *//** | ||
| * | ||
| * @file NativeRandomNumberGenerator_impl.hpp | ||
| * | ||
| *//* ----------------------------------------------------------------------- */ | ||
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| #ifndef MADLIB_POSTGRES_NATIVERANDOMNUMBERGENERATOR_IMPL_HPP | ||
| #define MADLIB_POSTGRES_NATIVERANDOMNUMBERGENERATOR_IMPL_HPP | ||
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| namespace madlib { | ||
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| namespace dbconnector { | ||
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| namespace postgres { | ||
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| inline | ||
| NativeRandomNumberGenerator::NativeRandomNumberGenerator() { } | ||
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| /** | ||
| * @brief Sets the current state of the engine | ||
| * | ||
| * All this function does is calling the backend's seed functions. | ||
| */ | ||
| inline | ||
| void | ||
| NativeRandomNumberGenerator::seed(result_type inSeed) { | ||
| DirectFunctionCall1(setseed, Float8GetDatum(inSeed)); | ||
| } | ||
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| /** | ||
| * @brief Advances the engine's state and returns the generated value | ||
| */ | ||
| inline | ||
| NativeRandomNumberGenerator::result_type | ||
| NativeRandomNumberGenerator::operator()() { | ||
| // There seems to be no DirectFunctionCall0(). | ||
| return DatumGetFloat8(DirectFunctionCall1(drandom, Datum(0))); | ||
| } | ||
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| /** | ||
| * @brief Return tight lower bound on the set of all values returned by | ||
| * <tt>operator()</tt> | ||
| */ | ||
| inline | ||
| NativeRandomNumberGenerator::result_type | ||
| NativeRandomNumberGenerator::min() { | ||
| return 0.0; | ||
| } | ||
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| /** | ||
| * @brief Return smallest representable number larger than maximum of all values | ||
| * returned by <tt>operator()</tt> | ||
| * | ||
| * Boost specifies, if \c result_type is not integer, then return "the smallest | ||
| * representable number larger than the tight upper bound on the set of all | ||
| * values returned by operator(). In any case, the return value of this function | ||
| * shall not change during the lifetime of the object." | ||
| * http://www.boost.org/doc/libs/1_50_0/doc/html/boost_random/reference.html | ||
| */ | ||
| inline | ||
| NativeRandomNumberGenerator::result_type | ||
| NativeRandomNumberGenerator::max() { | ||
| return 1.0; | ||
| } | ||
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| } // namespace postgres | ||
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| } // namespace dbconnector | ||
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| } // namespace madlib | ||
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| #endif // defined(MADLIB_POSTGRES_NATIVERANDOMNUMBERGENERATOR_IMPL_HPP) |
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