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new 74b3cdc4aa1 [chore](compile) fix some file complie warning error
(#55567)
74b3cdc4aa1 is described below
commit 74b3cdc4aa116a4f5b46ff49c7ef7a929346bc83
Author: zhangstar333 <[email protected]>
AuthorDate: Wed Sep 3 18:27:25 2025 +0800
[chore](compile) fix some file complie warning error (#55567)
### What problem does this PR solve?
fix some file complie warning error
---
be/src/util/jni-util.cpp | 9 +-
be/src/util/tdigest.h | 102 ++++++++++++---------
be/src/util/uid_util.cpp | 7 +-
be/src/util/url_parser.cpp | 5 +-
.../aggregate_function_percentile.h | 10 +-
5 files changed, 76 insertions(+), 57 deletions(-)
diff --git a/be/src/util/jni-util.cpp b/be/src/util/jni-util.cpp
index 6eb895f505d..55e95cb431c 100644
--- a/be/src/util/jni-util.cpp
+++ b/be/src/util/jni-util.cpp
@@ -22,11 +22,9 @@
#include <jni.h>
#include <jni_md.h>
-#include <algorithm>
#include <cstdlib>
#include <filesystem>
#include <iterator>
-#include <limits>
#include <memory>
#include <mutex>
#include <sstream>
@@ -34,6 +32,7 @@
#include <vector>
#include "absl/strings/substitute.h"
+#include "common/cast_set.h"
#include "common/config.h"
#include "util/doris_metrics.h"
#include "util/jni_native_method.h"
@@ -42,7 +41,7 @@
using std::string;
namespace doris {
-
+#include "common/compile_check_begin.h"
namespace {
JavaVM* g_vm;
[[maybe_unused]] std::once_flag g_vm_once;
@@ -146,7 +145,7 @@ const std::string GetKerb5ConfPath() {
JavaVMInitArgs vm_args;
vm_args.version = JNI_VERSION_1_8;
vm_args.options = jvm_options.get();
- vm_args.nOptions = options.size();
+ vm_args.nOptions = cast_set<int>(options.size());
// Set it to JNI_FALSE because JNI_TRUE will let JVM ignore the max
size config.
vm_args.ignoreUnrecognized = JNI_FALSE;
@@ -660,5 +659,5 @@ Status JniUtil::Init() {
DorisMetrics::instance()->init_jvm_metrics(env);
return Status::OK();
}
-
+#include "common/compile_check_end.h"
} // namespace doris
diff --git a/be/src/util/tdigest.h b/be/src/util/tdigest.h
index 30f07ae45c2..5dad6d5bac9 100644
--- a/be/src/util/tdigest.h
+++ b/be/src/util/tdigest.h
@@ -55,10 +55,9 @@
#include "common/factory_creator.h"
#include "common/logging.h"
-#include "udf/udf.h"
-#include "util/debug_util.h"
namespace doris {
+#include "common/compile_check_begin.h"
using Value = float;
using Weight = float;
@@ -106,7 +105,7 @@ struct CentroidList {
class CentroidListComparator {
public:
- CentroidListComparator() {}
+ CentroidListComparator() = default;
bool operator()(const CentroidList& left, const CentroidList& right) const
{
return left.iter->mean() > right.iter->mean();
@@ -125,7 +124,7 @@ class TDigest {
class TDigestComparator {
public:
- TDigestComparator() {}
+ TDigestComparator() = default;
bool operator()(const TDigest* left, const TDigest* right) const {
return left->totalSize() > right->totalSize();
@@ -230,7 +229,7 @@ public:
size_t totalSize = 0;
while (!pq.empty()) {
- auto td = pq.top();
+ const auto* td = pq.top();
batch.push_back(td);
pq.pop();
totalSize += td->totalSize();
@@ -258,7 +257,9 @@ public:
// return the cdf on the t-digest
Value cdf(Value x) {
- if (haveUnprocessed() || isDirty()) process();
+ if (haveUnprocessed() || isDirty()) {
+ process();
+ }
return cdfProcessed(x);
}
@@ -312,7 +313,8 @@ public:
// note that this is different than mean(0) > _min ... this
guarantees interpolation works
if (mean(0) - _min > 0) {
- return (x - _min) / (mean(0) - _min) * weight(0) /
_processed_weight / 2.0;
+ return static_cast<Value>((x - _min) / (mean(0) - _min) *
weight(0) /
+ _processed_weight / 2.0);
} else {
return 0;
}
@@ -324,8 +326,9 @@ public:
<< " _max " << _max << " mean(n - 1) " << mean(n
- 1) << " x " << x;
if (_max - mean(n - 1) > 0) {
- return 1.0 - (_max - x) / (_max - mean(n - 1)) * weight(n
- 1) /
- _processed_weight / 2.0;
+ return static_cast<Value>(1.0 - (_max - x) / (_max -
mean(n - 1)) *
+ weight(n - 1) /
_processed_weight /
+ 2.0);
} else {
return 1;
}
@@ -349,7 +352,9 @@ public:
// this returns a quantile on the t-digest
Value quantile(Value q) {
- if (haveUnprocessed() || isDirty()) process();
+ if (haveUnprocessed() || isDirty()) {
+ process();
+ }
return quantileProcessed(q);
}
@@ -379,12 +384,13 @@ public:
// at the boundaries, we return _min or _max
if (index <= weight(0) / 2.0) {
DCHECK_GT(weight(0), 0);
- return _min + 2.0 * index / weight(0) * (mean(0) - _min);
+ return static_cast<Value>(_min + 2.0 * index / weight(0) *
(mean(0) - _min));
}
auto iter = std::lower_bound(_cumulative.cbegin(), _cumulative.cend(),
index);
- if (iter + 1 != _cumulative.cend()) {
+ if (iter != _cumulative.cend() && iter != _cumulative.cbegin() &&
+ iter + 1 != _cumulative.cend()) {
auto i = std::distance(_cumulative.cbegin(), iter);
auto z1 = index - *(iter - 1);
auto z2 = *(iter)-index;
@@ -395,8 +401,8 @@ public:
DCHECK_LE(index, _processed_weight);
DCHECK_GE(index, _processed_weight - weight(n - 1) / 2.0);
- auto z1 = index - _processed_weight - weight(n - 1) / 2.0;
- auto z2 = weight(n - 1) / 2 - z1;
+ auto z1 = static_cast<Value>(index - _processed_weight - weight(n - 1)
/ 2.0);
+ auto z2 = static_cast<Value>(weight(n - 1) / 2 - z1);
return weightedAverage(mean(n - 1), z1, _max, z2);
}
@@ -412,7 +418,7 @@ public:
if (std::isnan(x)) {
return false;
}
- _unprocessed.push_back(Centroid(x, w));
+ _unprocessed.emplace_back(x, w);
_unprocessed_weight += w;
processIfNecessary();
return true;
@@ -424,7 +430,9 @@ public:
const size_t diff = std::distance(iter, end);
const size_t room = _max_unprocessed - _unprocessed.size();
auto mid = iter + std::min(diff, room);
- while (iter != mid) _unprocessed.push_back(*(iter++));
+ while (iter != mid) {
+ _unprocessed.push_back(*(iter++));
+ }
if (_unprocessed.size() >= _max_unprocessed) {
process();
}
@@ -432,9 +440,10 @@ public:
}
uint32_t serialized_size() {
- return sizeof(uint32_t) + sizeof(Value) * 5 + sizeof(Index) * 2 +
sizeof(uint32_t) * 3 +
- _processed.size() * sizeof(Centroid) + _unprocessed.size() *
sizeof(Centroid) +
- _cumulative.size() * sizeof(Weight);
+ return static_cast<uint32_t>(sizeof(uint32_t) + sizeof(Value) * 5 +
sizeof(Index) * 2 +
+ sizeof(uint32_t) * 3 + _processed.size()
* sizeof(Centroid) +
+ _unprocessed.size() * sizeof(Centroid) +
+ _cumulative.size() * sizeof(Weight));
}
size_t serialize(uint8_t* writer) {
@@ -457,7 +466,7 @@ public:
memcpy(writer, &_unprocessed_weight, sizeof(Value));
writer += sizeof(Value);
- uint32_t size = _processed.size();
+ auto size = static_cast<uint32_t>(_processed.size());
memcpy(writer, &size, sizeof(uint32_t));
writer += sizeof(uint32_t);
for (int i = 0; i < size; i++) {
@@ -465,7 +474,7 @@ public:
writer += sizeof(Centroid);
}
- size = _unprocessed.size();
+ size = static_cast<uint32_t>(_unprocessed.size());
memcpy(writer, &size, sizeof(uint32_t));
writer += sizeof(uint32_t);
//TODO(weixiang): may be once memcpy is enough!
@@ -474,7 +483,7 @@ public:
writer += sizeof(Centroid);
}
- size = _cumulative.size();
+ size = static_cast<uint32_t>(_cumulative.size());
memcpy(writer, &size, sizeof(uint32_t));
writer += sizeof(uint32_t);
for (int i = 0; i < size; i++) {
@@ -550,22 +559,24 @@ private:
std::vector<Weight> _cumulative;
// return mean of i-th centroid
- Value mean(int i) const noexcept { return _processed[i].mean(); }
+ Value mean(int64_t i) const noexcept { return _processed[i].mean(); }
// return weight of i-th centroid
- Weight weight(int i) const noexcept { return _processed[i].weight(); }
+ Weight weight(int64_t i) const noexcept { return _processed[i].weight(); }
// append all unprocessed centroids into current unprocessed vector
void mergeUnprocessed(const std::vector<const TDigest*>& tdigests) {
- if (tdigests.size() == 0) return;
+ if (tdigests.size() == 0) {
+ return;
+ }
size_t total = _unprocessed.size();
- for (auto& td : tdigests) {
+ for (const auto& td : tdigests) {
total += td->_unprocessed.size();
}
_unprocessed.reserve(total);
- for (auto& td : tdigests) {
+ for (const auto& td : tdigests) {
_unprocessed.insert(_unprocessed.end(), td->_unprocessed.cbegin(),
td->_unprocessed.cend());
_unprocessed_weight += td->_unprocessed_weight;
@@ -574,12 +585,14 @@ private:
// merge all processed centroids together into a single sorted vector
void mergeProcessed(const std::vector<const TDigest*>& tdigests) {
- if (tdigests.size() == 0) return;
+ if (tdigests.size() == 0) {
+ return;
+ }
size_t total = 0;
CentroidListQueue pq(CentroidListComparator {});
- for (auto& td : tdigests) {
- auto& sorted = td->_processed;
+ for (const auto& td : tdigests) {
+ const auto& sorted = td->_processed;
auto size = sorted.size();
if (size > 0) {
pq.push(CentroidList(sorted));
@@ -587,7 +600,9 @@ private:
_processed_weight += td->_processed_weight;
}
}
- if (total == 0) return;
+ if (total == 0) {
+ return;
+ }
if (_processed.size() > 0) {
pq.push(CentroidList(_processed));
@@ -602,7 +617,9 @@ private:
auto best = pq.top();
pq.pop();
sorted.push_back(*(best.iter));
- if (best.advance()) pq.push(best);
+ if (best.advance()) {
+ pq.push(best);
+ }
}
_processed = std::move(sorted);
if (_processed.size() > 0) {
@@ -621,10 +638,10 @@ private:
const auto n = _processed.size();
_cumulative.clear();
_cumulative.reserve(n + 1);
- auto previous = 0.0;
+ Weight previous = 0.0;
for (Index i = 0; i < n; i++) {
- auto current = weight(i);
- auto halfCurrent = current / 2.0;
+ Weight current = weight(i);
+ auto halfCurrent = static_cast<Weight>(current / 2.0);
_cumulative.push_back(previous + halfCurrent);
previous = previous + current;
}
@@ -654,14 +671,14 @@ private:
auto end = _unprocessed.end();
for (auto iter = _unprocessed.cbegin() + 1; iter < end; iter++) {
- auto& centroid = *iter;
+ const auto& centroid = *iter;
Weight projectedW = wSoFar + centroid.weight();
if (projectedW <= wLimit) {
wSoFar = projectedW;
(_processed.end() - 1)->add(centroid);
} else {
auto k1 = integratedLocation(wSoFar / _processed_weight);
- wLimit = _processed_weight * integratedQ(k1 + 1.0);
+ wLimit = _processed_weight * integratedQ(static_cast<Value>(k1
+ 1.0));
wSoFar += centroid.weight();
_processed.emplace_back(centroid);
}
@@ -674,8 +691,6 @@ private:
updateCumulative();
}
- int checkWeights() { return checkWeights(_processed, _processed_weight); }
-
size_t checkWeights(const std::vector<Centroid>& sorted, Value total) {
size_t badWeight = 0;
auto k1 = 0.0;
@@ -683,7 +698,7 @@ private:
for (auto iter = sorted.cbegin(); iter != sorted.cend(); iter++) {
auto w = iter->weight();
auto dq = w / total;
- auto k2 = integratedLocation(q + dq);
+ auto k2 = integratedLocation(static_cast<Value>(q + dq));
if (k2 - k1 > 1 && w != 1) {
VLOG_CRITICAL << "Oversize centroid at " <<
std::distance(sorted.cbegin(), iter)
<< " k1 " << k1 << " k2 " << k2 << " dk " << (k2
- k1) << " w " << w
@@ -721,11 +736,12 @@ private:
* @return The centroid scale value corresponding to q.
*/
Value integratedLocation(Value q) const {
- return _compression * (std::asin(2.0 * q - 1.0) + M_PI / 2) / M_PI;
+ return static_cast<Value>(_compression * (std::asin(2.0 * q - 1.0) +
M_PI / 2) / M_PI);
}
Value integratedQ(Value k) const {
- return (std::sin(std::min(k, _compression) * M_PI / _compression -
M_PI / 2) + 1) / 2;
+ return static_cast<Value>(
+ (std::sin(std::min(k, _compression) * M_PI / _compression -
M_PI / 2) + 1) / 2);
}
/**
@@ -773,5 +789,5 @@ private:
return previousMean * previousWeight + nextMean * nextWeight;
}
};
-
+#include "common/compile_check_end.h"
} // namespace doris
diff --git a/be/src/util/uid_util.cpp b/be/src/util/uid_util.cpp
index fb767f09bd7..e5254fffae2 100644
--- a/be/src/util/uid_util.cpp
+++ b/be/src/util/uid_util.cpp
@@ -24,12 +24,13 @@
#include <cstdlib>
+#include "common/cast_set.h"
#include "util/hash_util.hpp"
namespace doris {
-
+#include "common/compile_check_begin.h"
size_t UniqueId::hash(size_t seed) const {
- return doris::HashUtil::hash(this, sizeof(*this), seed);
+ return doris::HashUtil::hash(this, sizeof(*this),
cast_set<uint32_t>(seed));
}
std::size_t hash_value(const doris::TUniqueId& id) {
@@ -80,5 +81,5 @@ bool parse_id(const std::string& s, TUniqueId* id) {
*colon = ':';
return valid;
}
-
+#include "common/compile_check_end.h"
} // namespace doris
diff --git a/be/src/util/url_parser.cpp b/be/src/util/url_parser.cpp
index a0bdd153e6b..c51291fd15f 100644
--- a/be/src/util/url_parser.cpp
+++ b/be/src/util/url_parser.cpp
@@ -27,7 +27,7 @@
#include "vec/common/string_ref.h"
namespace doris {
-
+#include "common/compile_check_begin.h"
const StringRef UrlParser::_s_url_authority(const_cast<char*>("AUTHORITY"), 9);
const StringRef UrlParser::_s_url_file(const_cast<char*>("FILE"), 4);
const StringRef UrlParser::_s_url_host(const_cast<char*>("HOST"), 4);
@@ -402,7 +402,7 @@ StringRef UrlParser::extract_url(StringRef url, StringRef
name) {
// invalid url. like: k1&k2=bb
continue;
}
- int32_t key_len = key_url.size;
+ auto key_len = key_url.size;
auto key = key_url.substring(0, eq_pod);
if (name == key) {
return key_url.substring(eq_pod + 1, key_len - eq_pod - 1);
@@ -410,4 +410,5 @@ StringRef UrlParser::extract_url(StringRef url, StringRef
name) {
}
return result;
}
+#include "common/compile_check_end.h"
} // namespace doris
diff --git a/be/src/vec/aggregate_functions/aggregate_function_percentile.h
b/be/src/vec/aggregate_functions/aggregate_function_percentile.h
index 1578ec43a1c..f398dbebdc3 100644
--- a/be/src/vec/aggregate_functions/aggregate_function_percentile.h
+++ b/be/src/vec/aggregate_functions/aggregate_function_percentile.h
@@ -61,7 +61,7 @@ struct PercentileApproxState {
PercentileApproxState() = default;
~PercentileApproxState() = default;
- void init(double quantile, double compression = 10000) {
+ void init(double quantile, float compression = 10000) {
if (!init_flag) {
//https://doris.apache.org/zh-CN/sql-reference/sql-functions/aggregate-functions/percentile_approx.html#description
//The compression parameter setting range is [2048, 10000].
@@ -152,7 +152,7 @@ struct PercentileApproxState {
bool init_flag = false;
std::unique_ptr<TDigest> digest;
double target_quantile = INIT_QUANTILE;
- double compressions = 10000;
+ float compressions = 10000;
};
class AggregateFunctionPercentileApprox
@@ -230,7 +230,8 @@ public:
const auto& compression =
assert_cast<const ColumnFloat64&,
TypeCheckOnRelease::DISABLE>(*columns[2]);
- this->data(place).init(quantile.get_element(0),
compression.get_element(0));
+ this->data(place).init(quantile.get_element(0),
+ static_cast<float>(compression.get_element(0)));
this->data(place).add(sources.get_element(row_num));
}
@@ -302,7 +303,8 @@ public:
const auto& compression =
assert_cast<const ColumnFloat64&,
TypeCheckOnRelease::DISABLE>(*columns[3]);
- this->data(place).init(quantile.get_element(0),
compression.get_element(0));
+ this->data(place).init(quantile.get_element(0),
+ static_cast<float>(compression.get_element(0)));
this->data(place).add_with_weight(sources.get_element(row_num),
weight.get_element(row_num));
}
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