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Posted to commits@parquet.apache.org by uw...@apache.org on 2018/02/24 18:23:31 UTC
[parquet-cpp] branch master updated: PARQUET-1225: NaN values may lead to incorrect filtering under certai…
This is an automated email from the ASF dual-hosted git repository.
uwe pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/parquet-cpp.git
The following commit(s) were added to refs/heads/master by this push:
new 29a4b07 PARQUET-1225: NaN values may lead to incorrect filtering under certai…
29a4b07 is described below
commit 29a4b0741be4a510ecb346c708814caa98767915
Author: Deepak Majeti <de...@hpe.com>
AuthorDate: Sat Feb 24 19:23:23 2018 +0100
PARQUET-1225: NaN values may lead to incorrect filtering under certai…
1) `parquet-cpp` does not implement filtering (predicate pushdown). Clients such as Vertica, read the statistics from the metadata and implement their own filtering based on these stats.
Therefore, the read path does not require any changes. We should document that the min/max value can potentially contain NaNs.
2) I made changes to the write path to ignore the NaNs.
Author: Deepak Majeti <de...@hpe.com>
Closes #444 from majetideepak/PARQUET-1225 and squashes the following commits:
c29ede2 [Deepak Majeti] refactor code
c02adb2 [Deepak Majeti] fix compiler error
1c229e2 [Deepak Majeti] fix logic for UpdateSpaced
baf6f50 [Deepak Majeti] change api from NotNaN to IsNaN
3144a6a [Deepak Majeti] clang format
ba44611 [Deepak Majeti] review comments and add tests
63e889b [Deepak Majeti] PARQUET-1225: NaN values may lead to incorrect filtering under certain circumstances
---
src/parquet/statistics-test.cc | 119 ++++++++++++++++++++++++++++++++++++
src/parquet/statistics.cc | 133 +++++++++++++++++++++++++++++++----------
src/parquet/statistics.h | 1 +
3 files changed, 222 insertions(+), 31 deletions(-)
diff --git a/src/parquet/statistics-test.cc b/src/parquet/statistics-test.cc
index 1bbef26..5474016 100644
--- a/src/parquet/statistics-test.cc
+++ b/src/parquet/statistics-test.cc
@@ -659,5 +659,124 @@ TEST_F(TestStatisticsFLBA, UnknownSortOrder) {
ASSERT_FALSE(cc_metadata->is_stats_set());
}
+// PARQUET-1225: Float NaN values may lead to incorrect filtering under certain
+// circumstances
+TEST(TestStatisticsFloatNaN, NaNValues) {
+ constexpr int NUM_VALUES = 10;
+ NodePtr node = PrimitiveNode::Make("nan_float", Repetition::OPTIONAL, Type::FLOAT);
+ ColumnDescriptor descr(node, 1, 1);
+ float values[NUM_VALUES] = {std::nanf(""), -4.0f, -3.0f, -2.0f, -1.0f,
+ std::nanf(""), 1.0f, 2.0f, 3.0f, std::nanf("")};
+ float nan_values[NUM_VALUES];
+ for (int i = 0; i < NUM_VALUES; i++) {
+ nan_values[i] = std::nanf("");
+ }
+
+ // Test values
+ TypedRowGroupStatistics<FloatType> nan_stats(&descr);
+ nan_stats.Update(&values[0], NUM_VALUES, 0);
+ float min = nan_stats.min();
+ float max = nan_stats.max();
+ ASSERT_EQ(min, -4.0f);
+ ASSERT_EQ(max, 3.0f);
+
+ // Test all NaNs
+ TypedRowGroupStatistics<FloatType> all_nan_stats(&descr);
+ all_nan_stats.Update(&nan_values[0], NUM_VALUES, 0);
+ min = all_nan_stats.min();
+ max = all_nan_stats.max();
+ ASSERT_TRUE(std::isnan(min));
+ ASSERT_TRUE(std::isnan(max));
+
+ // Test values followed by all NaNs
+ nan_stats.Update(&nan_values[0], NUM_VALUES, 0);
+ min = nan_stats.min();
+ max = nan_stats.max();
+ ASSERT_EQ(min, -4.0f);
+ ASSERT_EQ(max, 3.0f);
+
+ // Test all NaNs followed by values
+ all_nan_stats.Update(&values[0], NUM_VALUES, 0);
+ min = all_nan_stats.min();
+ max = all_nan_stats.max();
+ ASSERT_EQ(min, -4.0f);
+ ASSERT_EQ(max, 3.0f);
+
+ // Test values followed by all NaNs followed by values
+ nan_stats.Update(&values[0], NUM_VALUES, 0);
+ min = nan_stats.min();
+ max = nan_stats.max();
+ ASSERT_EQ(min, -4.0f);
+ ASSERT_EQ(max, 3.0f);
+}
+
+// PARQUET-1225: Float NaN values may lead to incorrect filtering under certain
+// circumstances
+TEST(TestStatisticsFloatNaN, NaNValuesSpaced) {
+ constexpr int NUM_VALUES = 10;
+ NodePtr node = PrimitiveNode::Make("nan_float", Repetition::OPTIONAL, Type::FLOAT);
+ ColumnDescriptor descr(node, 1, 1);
+ float values[NUM_VALUES] = {std::nanf(""), -4.0f, -3.0f, -2.0f, -1.0f,
+ std::nanf(""), 1.0f, 2.0f, 3.0f, std::nanf("")};
+ float nan_values[NUM_VALUES];
+ for (int i = 0; i < NUM_VALUES; i++) {
+ nan_values[i] = std::nanf("");
+ }
+ std::vector<uint8_t> valid_bits(BitUtil::RoundUpNumBytes(NUM_VALUES) + 1, 255);
+
+ // Test values
+ TypedRowGroupStatistics<FloatType> nan_stats(&descr);
+ nan_stats.UpdateSpaced(&values[0], valid_bits.data(), 0, NUM_VALUES, 0);
+ float min = nan_stats.min();
+ float max = nan_stats.max();
+ ASSERT_EQ(min, -4.0f);
+ ASSERT_EQ(max, 3.0f);
+
+ // Test all NaNs
+ TypedRowGroupStatistics<FloatType> all_nan_stats(&descr);
+ all_nan_stats.UpdateSpaced(&nan_values[0], valid_bits.data(), 0, NUM_VALUES, 0);
+ min = all_nan_stats.min();
+ max = all_nan_stats.max();
+ ASSERT_TRUE(std::isnan(min));
+ ASSERT_TRUE(std::isnan(max));
+
+ // Test values followed by all NaNs
+ nan_stats.UpdateSpaced(&nan_values[0], valid_bits.data(), 0, NUM_VALUES, 0);
+ min = nan_stats.min();
+ max = nan_stats.max();
+ ASSERT_EQ(min, -4.0f);
+ ASSERT_EQ(max, 3.0f);
+
+ // Test all NaNs followed by values
+ all_nan_stats.UpdateSpaced(&values[0], valid_bits.data(), 0, NUM_VALUES, 0);
+ min = all_nan_stats.min();
+ max = all_nan_stats.max();
+ ASSERT_EQ(min, -4.0f);
+ ASSERT_EQ(max, 3.0f);
+
+ // Test values followed by all NaNs followed by values
+ nan_stats.UpdateSpaced(&values[0], valid_bits.data(), 0, NUM_VALUES, 0);
+ min = nan_stats.min();
+ max = nan_stats.max();
+ ASSERT_EQ(min, -4.0f);
+ ASSERT_EQ(max, 3.0f);
+}
+
+// NaN double values may lead to incorrect filtering under certain circumstances
+TEST(TestStatisticsDoubleNaN, NaNValues) {
+ constexpr int NUM_VALUES = 10;
+ NodePtr node = PrimitiveNode::Make("nan_double", Repetition::OPTIONAL, Type::DOUBLE);
+ ColumnDescriptor descr(node, 1, 1);
+ TypedRowGroupStatistics<DoubleType> nan_stats(&descr);
+ double values[NUM_VALUES] = {std::nan(""), std::nan(""), -3.0, -2.0, -1.0,
+ 0.0, 1.0, 2.0, 3.0, 4.0};
+ double* values_ptr = &values[0];
+ nan_stats.Update(values_ptr, NUM_VALUES, 0);
+ double min = nan_stats.min();
+ double max = nan_stats.max();
+
+ ASSERT_EQ(min, -3.0);
+ ASSERT_EQ(max, 4.0);
+}
} // namespace test
} // namespace parquet
diff --git a/src/parquet/statistics.cc b/src/parquet/statistics.cc
index 416557c..5b014ed 100644
--- a/src/parquet/statistics.cc
+++ b/src/parquet/statistics.cc
@@ -17,6 +17,7 @@
#include <algorithm>
#include <cstring>
+#include <type_traits>
#include "parquet/encoding-internal.h"
#include "parquet/exception.h"
@@ -97,6 +98,67 @@ void TypedRowGroupStatistics<DType>::Reset() {
}
template <typename DType>
+inline void TypedRowGroupStatistics<DType>::SetMinMax(const T& min, const T& max) {
+ if (!has_min_max_) {
+ has_min_max_ = true;
+ Copy(min, &min_, min_buffer_.get());
+ Copy(max, &max_, max_buffer_.get());
+ } else {
+ Copy(std::min(min_, min, std::ref(*(this->comparator_))), &min_, min_buffer_.get());
+ Copy(std::max(max_, max, std::ref(*(this->comparator_))), &max_, max_buffer_.get());
+ }
+}
+
+template <typename T, typename Enable = void>
+struct StatsHelper {
+ inline int64_t GetValueBeginOffset(const T* values, int64_t count) { return 0; }
+
+ inline int64_t GetValueEndOffset(const T* values, int64_t count) { return count; }
+
+ inline bool IsNaN(const T value) { return false; }
+};
+
+template <typename T>
+struct StatsHelper<T, typename std::enable_if<std::is_floating_point<T>::value>::type> {
+ inline int64_t GetValueBeginOffset(const T* values, int64_t count) {
+ // Skip NaNs
+ for (int64_t i = 0; i < count; i++) {
+ if (!std::isnan(values[i])) {
+ return i;
+ }
+ }
+ return count;
+ }
+
+ inline int64_t GetValueEndOffset(const T* values, int64_t count) {
+ // Skip NaNs
+ for (int64_t i = (count - 1); i >= 0; i--) {
+ if (!std::isnan(values[i])) {
+ return (i + 1);
+ }
+ }
+ return 0;
+ }
+
+ inline bool IsNaN(const T value) { return std::isnan(value); }
+};
+
+template <typename T>
+void SetNaN(T* value) {
+ // no-op
+}
+
+template <>
+void SetNaN<float>(float* value) {
+ *value = std::nanf("");
+}
+
+template <>
+void SetNaN<double>(double* value) {
+ *value = std::nan("");
+}
+
+template <typename DType>
void TypedRowGroupStatistics<DType>::Update(const T* values, int64_t num_not_null,
int64_t num_null) {
DCHECK(num_not_null >= 0);
@@ -107,18 +169,29 @@ void TypedRowGroupStatistics<DType>::Update(const T* values, int64_t num_not_nul
// TODO: support distinct count?
if (num_not_null == 0) return;
- auto batch_minmax =
- std::minmax_element(values, values + num_not_null, std::ref(*(this->comparator_)));
- if (!has_min_max_) {
- has_min_max_ = true;
- Copy(*batch_minmax.first, &min_, min_buffer_.get());
- Copy(*batch_minmax.second, &max_, max_buffer_.get());
- } else {
- Copy(std::min(min_, *batch_minmax.first, std::ref(*(this->comparator_))), &min_,
- min_buffer_.get());
- Copy(std::max(max_, *batch_minmax.second, std::ref(*(this->comparator_))), &max_,
- max_buffer_.get());
+ // PARQUET-1225: Handle NaNs
+ // The problem arises only if the starting/ending value(s)
+ // of the values-buffer contain NaN
+ StatsHelper<T> helper;
+ int64_t begin_offset = helper.GetValueBeginOffset(values, num_not_null);
+ int64_t end_offset = helper.GetValueEndOffset(values, num_not_null);
+
+ // All values are NaN
+ if (end_offset < begin_offset) {
+ // Set min/max to NaNs in this case.
+ // Don't set has_min_max flag since
+ // these values must be over-written by valid stats later
+ if (!has_min_max_) {
+ SetNaN(&min_);
+ SetNaN(&max_);
+ }
+ return;
}
+
+ auto batch_minmax = std::minmax_element(values + begin_offset, values + end_offset,
+ std::ref(*(this->comparator_)));
+
+ SetMinMax(*batch_minmax.first, *batch_minmax.second);
}
template <typename DType>
@@ -141,12 +214,26 @@ void TypedRowGroupStatistics<DType>::UpdateSpaced(const T* values,
int64_t i = 0;
::arrow::internal::BitmapReader valid_bits_reader(valid_bits, valid_bits_offset,
length);
+ StatsHelper<T> helper;
for (; i < length; i++) {
- if (valid_bits_reader.IsSet()) {
+ // PARQUET-1225: Handle NaNs
+ if (valid_bits_reader.IsSet() && !helper.IsNaN(values[i])) {
break;
}
valid_bits_reader.Next();
}
+
+ // All are NaNs and stats are not set yet
+ if ((i == length) && helper.IsNaN(values[i - 1])) {
+ // Don't set has_min_max flag since
+ // these values must be over-written by valid stats later
+ if (!has_min_max_) {
+ SetNaN(&min_);
+ SetNaN(&max_);
+ }
+ return;
+ }
+
T min = values[i];
T max = values[i];
for (; i < length; i++) {
@@ -159,14 +246,8 @@ void TypedRowGroupStatistics<DType>::UpdateSpaced(const T* values,
}
valid_bits_reader.Next();
}
- if (!has_min_max_) {
- has_min_max_ = true;
- Copy(min, &min_, min_buffer_.get());
- Copy(max, &max_, max_buffer_.get());
- } else {
- Copy(std::min(min_, min, std::ref(*(this->comparator_))), &min_, min_buffer_.get());
- Copy(std::max(max_, max, std::ref(*(this->comparator_))), &max_, max_buffer_.get());
- }
+
+ SetMinMax(min, max);
}
template <typename DType>
@@ -185,17 +266,7 @@ void TypedRowGroupStatistics<DType>::Merge(const TypedRowGroupStatistics<DType>&
if (!other.HasMinMax()) return;
- if (!has_min_max_) {
- Copy(other.min_, &this->min_, min_buffer_.get());
- Copy(other.max_, &this->max_, max_buffer_.get());
- has_min_max_ = true;
- return;
- }
-
- Copy(std::min(this->min_, other.min_, std::ref(*(this->comparator_))), &this->min_,
- min_buffer_.get());
- Copy(std::max(this->max_, other.max_, std::ref(*(this->comparator_))), &this->max_,
- max_buffer_.get());
+ SetMinMax(other.min_, other.max_);
}
template <typename DType>
diff --git a/src/parquet/statistics.h b/src/parquet/statistics.h
index b5466c0..36f9e44 100644
--- a/src/parquet/statistics.h
+++ b/src/parquet/statistics.h
@@ -159,6 +159,7 @@ class TypedRowGroupStatistics : public RowGroupStatistics {
void Update(const T* values, int64_t num_not_null, int64_t num_null);
void UpdateSpaced(const T* values, const uint8_t* valid_bits, int64_t valid_bits_spaced,
int64_t num_not_null, int64_t num_null);
+ void SetMinMax(const T& min, const T& max);
const T& min() const;
const T& max() const;
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