diff --git a/src/AggregateFunctions/QuantileTDigest.h b/src/AggregateFunctions/QuantileTDigest.h
index 02d43ede66d..c09797573c4 100644
--- a/src/AggregateFunctions/QuantileTDigest.h
+++ b/src/AggregateFunctions/QuantileTDigest.h
@@ -40,6 +40,7 @@ class TDigest
 {
     using Value = Float32;
     using Count = Float32;
+    using BetterFloat = Float64; // For intermediate results and sum(Count). Must have better precision, than Count
 
     /** The centroid stores the weight of points around their mean value
       */
@@ -55,13 +56,6 @@ class TDigest
             , count(count_)
         {}
 
-        Centroid & operator+=(const Centroid & other)
-        {
-            count += other.count;
-            mean += other.count * (other.mean - mean) / count;
-            return *this;
-        }
-
         bool operator<(const Centroid & other) const
         {
             return mean < other.mean;
@@ -89,8 +83,8 @@ class TDigest
     using Centroids = PODArrayWithStackMemory<Centroid, bytes_in_arena>;
 
     Centroids centroids;
-    Count count = 0;
-    UInt32 unmerged = 0;
+    BetterFloat count = 0;
+    size_t unmerged = 0;
 
     struct RadixSortTraits
     {
@@ -111,6 +105,7 @@ class TDigest
     };
 
     /** Adds a centroid `c` to the digest
+     * centroid must be valid, validity is checked in add(), deserialize() and is maintained by compress()
       */
     void addCentroid(const Centroid & c)
     {
@@ -138,47 +133,63 @@ public:
                 auto l = centroids.begin();
                 auto r = std::next(l);
 
-                Count sum = 0;
+                const BetterFloat count_epsilon_4 = count * params.epsilon * 4; // Compiler is unable to do this optimization
+                BetterFloat sum = 0;
+                BetterFloat l_mean = l->mean; // We have high-precision temporaries for numeric stability
+                BetterFloat l_count = l->count;
                 while (r != centroids.end())
                 {
+                    if (l->mean == r->mean) // Perfect aggregation (fast). We compare l->mean, not l_mean, to avoid identical elements after compress
+                    {
+                        l_count += r->count;
+                        l->count = l_count;
+                        ++r;
+                        continue;
+                    }
                     // we use quantile which gives us the smallest error
 
                     /// The ratio of the part of the histogram to l, including the half l to the entire histogram. That is, what level quantile in position l.
-                    Value ql = (sum + l->count * 0.5) / count;
-                    Value err = ql * (1 - ql);
+                    BetterFloat ql = (sum + l_count * 0.5) / count;
+                    BetterFloat err = ql * (1 - ql);
 
                     /// The ratio of the portion of the histogram to l, including l and half r to the entire histogram. That is, what level is the quantile in position r.
-                    Value qr = (sum + l->count + r->count * 0.5) / count;
-                    Value err2 = qr * (1 - qr);
+                    BetterFloat qr = (sum + l_count + r->count * 0.5) / count;
+                    BetterFloat err2 = qr * (1 - qr);
 
                     if (err > err2)
                         err = err2;
 
-                    Value k = 4 * count * err * params.epsilon;
+                    BetterFloat k = count_epsilon_4 * err;
 
                     /** The ratio of the weight of the glued column pair to all values is not greater,
                       *  than epsilon multiply by a certain quadratic coefficient, which in the median is 1 (4 * 1/2 * 1/2),
                       *  and at the edges decreases and is approximately equal to the distance to the edge * 4.
                       */
 
-                    if (l->count + r->count <= k)
+                    if (l_count + r->count <= k)
                     {
                         // it is possible to merge left and right
                         /// The left column "eats" the right.
-                        *l += *r;
+                        l_count += r->count;
+                        l_mean += r->count * (r->mean - l_mean) / l_count; // Symmetric algo (M1*C1 + M2*C2)/(C1+C2) is numerically better, but slower
+                        l->mean = l_mean;
+                        l->count = l_count;
                     }
                     else
                     {
                         // not enough capacity, check the next pair
-                        sum += l->count;
+                        sum += l->count; // Not l_count, otherwise actual sum of elements will be different
                         ++l;
 
                         /// We skip all the values "eaten" earlier.
                         if (l != r)
                             *l = *r;
+                        l_mean = l->mean;
+                        l_count = l->count;
                     }
                     ++r;
                 }
+                count = sum + l_count; // Update count, changed due inaccurancy
 
                 /// At the end of the loop, all values to the right of l were "eaten".
                 centroids.resize(l - centroids.begin() + 1);
@@ -192,6 +203,8 @@ public:
       */
     void add(T x, UInt64 cnt = 1)
     {
+        if (cnt == 0)
+            return; // Count 0 breaks compress() assumptions
         addCentroid(Centroid(Value(x), Count(cnt)));
     }
 
@@ -220,8 +233,16 @@ public:
         buf.read(reinterpret_cast<char *>(centroids.data()), size * sizeof(centroids[0]));
 
         count = 0;
-        for (const auto & c : centroids)
+        for (size_t i = 0; i != centroids.size(); ++i)
+        {
+            Centroid & c = centroids[i];
+            if (c.count <= 0 || std::isnan(c.count) || std::isnan(c.mean)) // invalid count breaks compress(), invalid mean breaks sort()
+            {
+                centroids.resize(i); // Exception safety, without this line we will end up with TDigest with invalid centroids
+                throw std::runtime_error("Invalid centroid " + std::to_string(c.count) + ":" + std::to_string(c.mean));
+            }
             count += c.count;
+        }
     }
 
     Count getCount()