Privacy-on-Beam: support for quantiles, C++ accounting: fast delta

C++ DP Lib:
  * Migrated to absl::Status

Privacy-on-Beam:
  * Implement QuantilesPerKey along with pbeamtest support
  * Updated dependencies

C++ accounting library:
  * Fast computation of delta without convolution

GitOrigin-RevId: 9faba9cd2873465e0f52bc2f9304dd9fa27e6998
Change-Id: I908cb6281e0316be82ae7264a6a79dc3ac126f03

cc/accounting/privacy_loss_distribution.cc

@@ -21,6 +21,7 @@
 #include "absl/strings/str_format.h"
 #include "accounting/common/common.h"
 #include "accounting/convolution.h"
+#include "base/status_macros.h"
 
 namespace differential_privacy {
 namespace accounting {
@@ -206,8 +207,8 @@ PrivacyLossDistribution::CreateForPrivacyParameters(
       discretization_interval, /*infinity_mass=*/delta, rounded_pmf));
 }
 
-absl::Status PrivacyLossDistribution::Compose(
-    const PrivacyLossDistribution& other_pld, double tail_mass_truncation) {
+absl::Status PrivacyLossDistribution::ValidateComposition(
+    const PrivacyLossDistribution& other_pld) const {
   if (other_pld.DiscretizationInterval() != discretization_interval_) {
     return absl::InvalidArgumentError(absl::StrFormat(
         "Cannot compose, discretization intervals are different "
@@ -220,6 +221,13 @@ absl::Status PrivacyLossDistribution::Compose(
         "Cannot compose, estimate types are different");
   }
 
+  return absl::OkStatus();
+}
+
+absl::Status PrivacyLossDistribution::Compose(
+    const PrivacyLossDistribution& other_pld, double tail_mass_truncation) {
+  RETURN_IF_ERROR(ValidateComposition(other_pld));
+
   double new_infinity_mass = infinity_mass_ + other_pld.InfinityMass() -
                              infinity_mass_ * other_pld.InfinityMass();
 
@@ -237,6 +245,51 @@ absl::Status PrivacyLossDistribution::Compose(
   return absl::OkStatus();
 }
 
+base::StatusOr<double>
+PrivacyLossDistribution::GetDeltaForEpsilonForComposedPLD(
+    const PrivacyLossDistribution& other_pld, double epsilon) const {
+  RETURN_IF_ERROR(ValidateComposition(other_pld));
+
+  UnpackedProbabilityMassFunction this_pmf =
+      UnpackProbabilityMassFunction(probability_mass_function_);
+  UnpackedProbabilityMassFunction other_pmf =
+      UnpackProbabilityMassFunction(other_pld.probability_mass_function_);
+
+  // Compute the hockey stick divergence using equation (2) in the
+  // supplementary material. other_cumulative_upper_mass below represents the
+  // summation in equation (3) and other_cumulative_lower_mass represents the
+  // summation in equation (4).
+
+  double other_cumulative_upper_mass = 0;
+  double other_cumulative_lower_mass = 0;
+  int current_idx = other_pmf.items.size() - 1;
+  double delta = 0;
+
+  for (int this_idx = 0; this_idx < this_pmf.items.size(); ++this_idx) {
+    double this_privacy_loss =
+        discretization_interval_ * (this_idx + this_pmf.min_key);
+    double this_probability_mass = this_pmf.items[this_idx];
+    while (current_idx >= 0) {
+      double other_privacy_loss = other_pld.discretization_interval_ *
+                                  (current_idx + other_pmf.min_key);
+      if (other_privacy_loss + this_privacy_loss <= epsilon) break;
+      other_cumulative_upper_mass += other_pmf.items[current_idx];
+      other_cumulative_lower_mass +=
+          other_pmf.items[current_idx] / std::exp(other_privacy_loss);
+      --current_idx;
+    }
+    delta += this_probability_mass * (other_cumulative_upper_mass -
+                                      std::exp(epsilon - this_privacy_loss) *
+                                          other_cumulative_lower_mass);
+  }
+
+  // The probability that the composed privacy loss is infinite.
+  double composed_infinity_mass = infinity_mass_ + other_pld.InfinityMass() -
+                                  infinity_mass_ * other_pld.InfinityMass();
+
+  return delta + composed_infinity_mass;
+}
+
 void PrivacyLossDistribution::Compose(int num_times) {
   double new_infinity_mass = 1 - pow((1 - infinity_mass_), num_times);
 

cc/accounting/privacy_loss_distribution.h

@@ -146,13 +146,27 @@ class PrivacyLossDistribution {
   // Observation 1 in the supplementary material.)
   double GetEpsilonForDelta(double delta) const;
 
-  // Composes other PLD into itself. The discretization intervals should be
-  // the same otherwise failure status is returned. Additional parameter:
+  // Validates that a given PLD can be composed with this PLD. The
+  // discretization intervals and the estimate types should be the same;
+  // otherwise failure status is returned.
+  absl::Status ValidateComposition(
+      const PrivacyLossDistribution& other_pld) const;
+
+  // Composes other PLD into itself. Additional parameter:
   //   tail_mass_truncation: an upper bound on the tails of the probability
   //     mass of the PLD that might be truncated.
   absl::Status Compose(const PrivacyLossDistribution& other_pld,
                        double tail_mass_truncation = 1e-15);
 
+  // Computes delta for given epsilon for the result of composing this PLD and a
+  // given PLD. Note that this function does not modify the current PLD.
+  //
+  // The output of this function should be the same as first composing this PLD
+  // and other_pld, and then call GetEpsilonForDelta on the resulting
+  // PLD. The main advantage is that this function is faster.
+  base::StatusOr<double> GetDeltaForEpsilonForComposedPLD(
+      const PrivacyLossDistribution& other_pld, double epsilon) const;
+
   // Composes PLD into itself num_times.
   void Compose(int num_times);
 

cc/accounting/privacy_loss_distribution_test.cc

@@ -160,6 +160,25 @@ TEST(PrivacyLossDistributionTest, Compose) {
   EXPECT_FALSE(pld->Pmf().empty());
 }
 
+TEST(PrivacyLossDistributionTest, GetDeltaForEpsilonForComposedPLD) {
+  ProbabilityMassFunction pmf = {{0, 0.1}, {1, 0.7}, {2, 0.1}};
+  std::unique_ptr<PrivacyLossDistribution> pld =
+      PrivacyLossDistributionTestPeer::Create(pmf,
+                                              /*infinity_mass=*/0.1,
+                                              /*discretization_interval=*/0.4);
+
+  ProbabilityMassFunction pmf_other = {{1, 0.1}, {2, 0.6}, {3, 0.25}};
+  std::unique_ptr<PrivacyLossDistribution> pld_other =
+      PrivacyLossDistributionTestPeer::Create(pmf_other,
+                                              /*infinity_mass=*/0.05,
+                                              /*discretization_interval=*/0.4);
+
+  base::StatusOr<double> delta =
+      pld->GetDeltaForEpsilonForComposedPLD(*pld_other, /*epsilon=*/1.1);
+  ASSERT_OK(delta);
+  EXPECT_THAT(*delta, DoubleNear(0.2956, kMaxError));
+}
+
 TEST(PrivacyLossDistributionTest, ComposeTruncation) {
   ProbabilityMassFunction pmf = {{0, 0.1}, {1, 0.7}, {2, 0.1}};
   std::unique_ptr<PrivacyLossDistribution> pld =
@@ -209,10 +228,16 @@ TEST(PrivacyLossDistributionTest,
   std::unique_ptr<PrivacyLossDistribution> pld_other =
       PrivacyLossDistributionTestPeer::Create(pmf, 0.3, 2e-4);
 
-  EXPECT_THAT(pld->Compose(*pld_other),
-              StatusIs(absl::InvalidArgumentError("").code(),
-                       HasSubstr("Cannot compose, discretization intervals "
-                                 "are different - 0.000200 vs 0.000100")));
+  std::string error_msg = "discretization interval";
+  EXPECT_THAT(
+      pld->ValidateComposition(*pld_other),
+      StatusIs(absl::StatusCode::kInvalidArgument, HasSubstr(error_msg)));
+  EXPECT_THAT(
+      pld->Compose(*pld_other),
+      StatusIs(absl::StatusCode::kInvalidArgument, HasSubstr(error_msg)));
+  EXPECT_THAT(
+      pld->GetDeltaForEpsilonForComposedPLD(*pld_other, /*epsilon=*/1),
+      StatusIs(absl::StatusCode::kInvalidArgument, HasSubstr(error_msg)));
 }
 
 TEST(PrivacyLossDistributionTest, ComposeErrorDifferentEstimateTypes) {
@@ -227,9 +252,16 @@ TEST(PrivacyLossDistributionTest, ComposeErrorDifferentEstimateTypes) {
           pmf, /*infinity_mass=*/0.3, /*discretization_interval=*/1e-4,
           /*estimate_type=*/EstimateType::kOptimistic);
 
-  EXPECT_THAT(pld->Compose(*pld_other),
-              StatusIs(absl::StatusCode::kInvalidArgument,
-                       Eq("Cannot compose, estimate types are different")));
+  std::string error_msg = "estimate type";
+  EXPECT_THAT(
+      pld->ValidateComposition(*pld_other),
+      StatusIs(absl::StatusCode::kInvalidArgument, HasSubstr(error_msg)));
+  EXPECT_THAT(
+      pld->Compose(*pld_other),
+      StatusIs(absl::StatusCode::kInvalidArgument, HasSubstr(error_msg)));
+  EXPECT_THAT(
+      pld->GetDeltaForEpsilonForComposedPLD(*pld_other, /*epsilon=*/1),
+      StatusIs(absl::StatusCode::kInvalidArgument, HasSubstr(error_msg)));
 }
 
 struct GetEpsilonFromDeltaParam {

cc/algorithms/BUILD

@@ -486,6 +486,7 @@ cc_library(
         "//base:logging",
         "@boringssl//:crypto",
         "@com_google_absl//absl/base:core_headers",
+        "@com_google_absl//absl/numeric:bits",
         "@com_google_absl//absl/synchronization",
     ],
 )

cc/algorithms/rand.cc

@@ -23,21 +23,12 @@
 #include <limits>
 
 #include "base/logging.h"
+#include "absl/numeric/bits.h"
 #include "absl/synchronization/mutex.h"
 #include "openssl/rand.h"
 
 namespace differential_privacy {
 namespace {
-// From absl/base/internal/bits.h.
-int CountLeadingZeros64Slow(uint64_t n) {
-  int zeroes = 60;
-  if (n >> 32) zeroes -= 32, n >>= 32;
-  if (n >> 16) zeroes -= 16, n >>= 16;
-  if (n >> 8) zeroes -= 8, n >>= 8;
-  if (n >> 4) zeroes -= 4, n >>= 4;
-  return "\4\3\2\2\1\1\1\1\0\0\0\0\0\0\0"[n] + zeroes;
-}
-
 // We usually expect DBL_MANT_DIG to be 53.
 static_assert(DBL_MANT_DIG < 64,
               "Double mantissa must have less than 64 bits.");
@@ -59,7 +50,7 @@ double UniformDouble() {
   uint64_t j = uint_64_number >> kMantDigits;
 
   // exponent is the number of leading zeros in the first 11 bits plus one.
-  uint64_t exponent = CountLeadingZeros64Slow(j) - kMantDigits + 1;
+  uint64_t exponent = absl::countl_zero(j) - kMantDigits + 1;
 
   // Extra geometric sampling is needed only when the leading 11 bits are all 0.
   if (j == 0) {
@@ -84,7 +75,7 @@ uint64_t Geometric() {
   uint64_t r = 0;
   while (r == 0 && result < 1023) {
     r = SecureURBG::GetSingleton()();
-    result += CountLeadingZeros64Slow(r);
+    result += absl::countl_zero(r);
   }
   return result;
 }

cc/cc_differential_privacy_deps.bzl

@@ -27,9 +27,9 @@ def cc_differential_privacy_deps():
     # Abseil
     http_archive(
         name = "com_google_absl",
-        url = "https://github.com/abseil/abseil-cpp/archive/20200923.3.tar.gz",
-        sha256 = "ebe2ad1480d27383e4bf4211e2ca2ef312d5e6a09eba869fd2e8a5c5d553ded2",
-        strip_prefix = "abseil-cpp-20200923.3",
+        url = "https://github.com/abseil/abseil-cpp/archive/20210324.0.tar.gz",
+        sha256 = "dd7db6815204c2a62a2160e32c55e97113b0a0178b2f090d6bab5ce36111db4b",
+        strip_prefix = "abseil-cpp-20210324.0",
     )
 
     # Common bazel rules

cc/docs/algorithms/algorithm.md

@@ -110,7 +110,7 @@ an error.
 
 ```
 Summary Serialize();
-util::Status Merge(const Summary& summary);
+absl::Status Merge(const Summary& summary);
 ```
 
 Serialization and merging can allow these algorithms to be used in a distributed

cc/postgres/postgres.BUILD

@@ -15,7 +15,7 @@
 
 licenses(["notice"])  # Apache v2.0
 
-load("@rules_foreign_cc//tools/build_defs:configure.bzl", "configure_make")
+load("@rules_foreign_cc//foreign_cc:configure.bzl", "configure_make")
 
 package(
     default_visibility = ["//visibility:public"],
@@ -50,7 +50,7 @@ configure_make(
             "CFLAGS": "-fPIC",
         },
     }),
-    headers_only = True,
+    out_headers_only = True,
     lib_source = "@postgres//:all",
 )
 

cc/testing/stochastic_tester_test.cc

@@ -51,8 +51,8 @@ class NonDpSum : public Algorithm<T> {
   void ResetState() override { result_ = 0; }
 
   Summary Serialize() const override { return Summary(); }
-  base::Status Merge(const Summary& summary) override {
-    return base::OkStatus();
+  absl::Status Merge(const Summary& summary) override {
+    return absl::OkStatus();
   }
   int64_t MemoryUsed() override { return sizeof(NonDpSum<T>); };
 
@@ -74,8 +74,8 @@ class NonDpCount : public Algorithm<T> {
   void ResetState() override { result_ = 0; }
 
   Summary Serialize() const override { return Summary(); }
-  base::Status Merge(const Summary& summary) override {
-    return base::OkStatus();
+  absl::Status Merge(const Summary& summary) override {
+    return absl::OkStatus();
   }
   int64_t MemoryUsed() override { return sizeof(NonDpCount<T>); };
 
@@ -166,8 +166,8 @@ class AlwaysError : public Algorithm<T> {
   void ResetState() override {}
 
   Summary Serialize() const override { return Summary(); }
-  base::Status Merge(const Summary& summary) override {
-    return base::OkStatus();
+  absl::Status Merge(const Summary& summary) override {
+    return absl::OkStatus();
   }
   int64_t MemoryUsed() override { return sizeof(AlwaysError<T>); };
 

go/dpagg/quantiles.go

@@ -25,10 +25,11 @@ import (
 	"github.com/google/differential-privacy/go/noise"
 )
 
+// Constants used for QuantileTrees.
 const (
 	numericalTolerance     = 1e-6
-	defaultTreeHeight      = 4
-	defaultBranchingFactor = 16
+	DefaultTreeHeight      = 4
+	DefaultBranchingFactor = 16
 	rootIndex              = 0
 	// Fraction a node needs to contribute to the total count of itself and its siblings to be
 	// considered during the search for a particular quantile. The idea of alpha is to filter out
@@ -61,7 +62,7 @@ type BoundedQuantiles struct {
 	branchingFactor int
 	l0Sensitivity   int64
 	lInfSensitivity float64
-	noise           noise.Noise
+	Noise           noise.Noise
 	noiseKind       noise.Kind // necessary for serializing noise.Noise information
 
 	// State variables
@@ -128,15 +129,15 @@ func NewBoundedQuantiles(opt *BoundedQuantilesOptions) *BoundedQuantiles {
 	// Check tree height and branching factor, set defaults if not specified, and use them to compute numLeaves and leftmostLeafIndex.
 	treeHeight := opt.TreeHeight
 	if treeHeight == 0 {
-		treeHeight = defaultTreeHeight
+		treeHeight = DefaultTreeHeight
 	}
 	if err := checks.CheckTreeHeight("NewBoundedQuantiles", treeHeight); err != nil {
 		// TODO: do not exit the program from within library code
 		log.Fatalf("CheckTreeHeight failed with %v", err)
 	}
 	branchingFactor := opt.BranchingFactor
 	if branchingFactor == 0 {
-		branchingFactor = defaultBranchingFactor
+		branchingFactor = DefaultBranchingFactor
 	}
 	if err := checks.CheckBranchingFactor("NewBoundedQuantiles", branchingFactor); err != nil {
 		// TODO: do not exit the program from within library code
@@ -171,7 +172,7 @@ func NewBoundedQuantiles(opt *BoundedQuantilesOptions) *BoundedQuantiles {
 		branchingFactor:   branchingFactor,
 		l0Sensitivity:     l0Sensitivity,
 		lInfSensitivity:   lInfSensitivity,
-		noise:             n,
+		Noise:             n,
 		noiseKind:         noise.ToKind(n),
 		tree:              make(map[int]int64),
 		noisedTree:        make(map[int]float64),
@@ -328,7 +329,7 @@ func (bq *BoundedQuantiles) getNoisedCount(index int) float64 {
 		return noisedCount
 	}
 	rawCount := bq.tree[index]
-	noisedCount := bq.noise.AddNoiseFloat64(float64(rawCount), bq.l0Sensitivity, bq.lInfSensitivity, bq.epsilon, bq.delta)
+	noisedCount := bq.Noise.AddNoiseFloat64(float64(rawCount), bq.l0Sensitivity, bq.lInfSensitivity, bq.epsilon, bq.delta)
 	bq.noisedTree[index] = noisedCount
 	return noisedCount
 }
@@ -359,6 +360,7 @@ func (bq *BoundedQuantiles) Merge(bq2 *BoundedQuantiles) {
 	for index, count := range bq2.tree {
 		bq.tree[index] += count
 	}
+	bq2.state = merged
 }
 
 func checkMergeBoundedQuantiles(bq1, bq2 *BoundedQuantiles) error {
@@ -421,7 +423,7 @@ func (bq *BoundedQuantiles) GobEncode() ([]byte, error) {
 		Upper:             bq.upper,
 		NumLeaves:         bq.numLeaves,
 		LeftmostLeafIndex: bq.leftmostLeafIndex,
-		NoiseKind:         noise.ToKind(bq.noise),
+		NoiseKind:         noise.ToKind(bq.Noise),
 		QuantileTree:      bq.tree,
 	}
 	bq.state = serialized
@@ -446,7 +448,7 @@ func (bq *BoundedQuantiles) GobDecode(data []byte) error {
 		lower:             enc.Lower,
 		upper:             enc.Upper,
 		noiseKind:         enc.NoiseKind,
-		noise:             noise.ToNoise(enc.NoiseKind),
+		Noise:             noise.ToNoise(enc.NoiseKind),
 		numLeaves:         enc.NumLeaves,
 		leftmostLeafIndex: enc.LeftmostLeafIndex,
 		tree:              enc.QuantileTree,