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hash_join_node_test.cc
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hash_join_node_test.cc
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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
#include <gmock/gmock-matchers.h>
#include <random>
#include <unordered_set>
#include "arrow/api.h"
#include "arrow/compute/exec/options.h"
#include "arrow/compute/exec/test_util.h"
#include "arrow/compute/exec/util.h"
#include "arrow/compute/kernels/row_encoder.h"
#include "arrow/compute/kernels/test_util.h"
#include "arrow/testing/gtest_util.h"
#include "arrow/testing/matchers.h"
#include "arrow/testing/random.h"
#include "arrow/util/checked_cast.h"
#include "arrow/util/make_unique.h"
#include "arrow/util/pcg_random.h"
#include "arrow/util/thread_pool.h"
using testing::UnorderedElementsAreArray;
namespace arrow {
namespace compute {
BatchesWithSchema GenerateBatchesFromString(
const std::shared_ptr<Schema>& schema,
const std::vector<util::string_view>& json_strings, int multiplicity = 1) {
BatchesWithSchema out_batches{{}, schema};
std::vector<ValueDescr> descrs;
for (auto&& field : schema->fields()) {
descrs.emplace_back(field->type());
}
for (auto&& s : json_strings) {
out_batches.batches.push_back(ExecBatchFromJSON(descrs, s));
}
size_t batch_count = out_batches.batches.size();
for (int repeat = 1; repeat < multiplicity; ++repeat) {
for (size_t i = 0; i < batch_count; ++i) {
out_batches.batches.push_back(out_batches.batches[i]);
}
}
return out_batches;
}
void CheckRunOutput(JoinType type, const BatchesWithSchema& l_batches,
const BatchesWithSchema& r_batches,
const std::vector<FieldRef>& left_keys,
const std::vector<FieldRef>& right_keys,
const BatchesWithSchema& exp_batches, bool parallel = false) {
auto exec_ctx = arrow::internal::make_unique<ExecContext>(
default_memory_pool(), parallel ? arrow::internal::GetCpuThreadPool() : nullptr);
ASSERT_OK_AND_ASSIGN(auto plan, ExecPlan::Make(exec_ctx.get()));
HashJoinNodeOptions join_options{type, left_keys, right_keys};
Declaration join{"hashjoin", join_options};
// add left source
join.inputs.emplace_back(Declaration{
"source", SourceNodeOptions{l_batches.schema, l_batches.gen(parallel,
/*slow=*/false)}});
// add right source
join.inputs.emplace_back(Declaration{
"source", SourceNodeOptions{r_batches.schema, r_batches.gen(parallel,
/*slow=*/false)}});
AsyncGenerator<util::optional<ExecBatch>> sink_gen;
ASSERT_OK(Declaration::Sequence({join, {"sink", SinkNodeOptions{&sink_gen}}})
.AddToPlan(plan.get()));
ASSERT_FINISHES_OK_AND_ASSIGN(auto res, StartAndCollect(plan.get(), sink_gen));
ASSERT_OK_AND_ASSIGN(auto exp_table,
TableFromExecBatches(exp_batches.schema, exp_batches.batches));
ASSERT_OK_AND_ASSIGN(auto out_table, TableFromExecBatches(exp_batches.schema, res));
if (exp_table->num_rows() == 0) {
ASSERT_EQ(exp_table->num_rows(), out_table->num_rows());
} else {
std::vector<SortKey> sort_keys;
for (auto&& f : exp_batches.schema->fields()) {
sort_keys.emplace_back(f->name());
}
ASSERT_OK_AND_ASSIGN(auto exp_table_sort_ids,
SortIndices(exp_table, SortOptions(sort_keys)));
ASSERT_OK_AND_ASSIGN(auto exp_table_sorted, Take(exp_table, exp_table_sort_ids));
ASSERT_OK_AND_ASSIGN(auto out_table_sort_ids,
SortIndices(out_table, SortOptions(sort_keys)));
ASSERT_OK_AND_ASSIGN(auto out_table_sorted, Take(out_table, out_table_sort_ids));
AssertTablesEqual(*exp_table_sorted.table(), *out_table_sorted.table(),
/*same_chunk_layout=*/false, /*flatten=*/true);
}
}
void RunNonEmptyTest(JoinType type, bool parallel) {
auto l_schema = schema({field("l_i32", int32()), field("l_str", utf8())});
auto r_schema = schema({field("r_str", utf8()), field("r_i32", int32())});
BatchesWithSchema l_batches, r_batches, exp_batches;
int multiplicity = parallel ? 100 : 1;
l_batches = GenerateBatchesFromString(
l_schema,
{R"([[0,"d"], [1,"b"]])", R"([[2,"d"], [3,"a"], [4,"a"]])",
R"([[5,"b"], [6,"c"], [7,"e"], [8,"e"]])"},
multiplicity);
r_batches = GenerateBatchesFromString(
r_schema,
{R"([["f", 0], ["b", 1], ["b", 2]])", R"([["c", 3], ["g", 4]])", R"([["e", 5]])"},
multiplicity);
switch (type) {
case JoinType::LEFT_SEMI:
exp_batches = GenerateBatchesFromString(
l_schema, {R"([[1,"b"]])", R"([])", R"([[5,"b"], [6,"c"], [7,"e"], [8,"e"]])"},
multiplicity);
break;
case JoinType::RIGHT_SEMI:
exp_batches = GenerateBatchesFromString(
r_schema, {R"([["b", 1], ["b", 2]])", R"([["c", 3]])", R"([["e", 5]])"},
multiplicity);
break;
case JoinType::LEFT_ANTI:
exp_batches = GenerateBatchesFromString(
l_schema, {R"([[0,"d"]])", R"([[2,"d"], [3,"a"], [4,"a"]])", R"([])"},
multiplicity);
break;
case JoinType::RIGHT_ANTI:
exp_batches = GenerateBatchesFromString(
r_schema, {R"([["f", 0]])", R"([["g", 4]])", R"([])"}, multiplicity);
break;
case JoinType::INNER:
case JoinType::LEFT_OUTER:
case JoinType::RIGHT_OUTER:
case JoinType::FULL_OUTER:
default:
FAIL() << "join type not implemented!";
}
CheckRunOutput(type, l_batches, r_batches,
/*left_keys=*/{{"l_str"}}, /*right_keys=*/{{"r_str"}}, exp_batches,
parallel);
}
void RunEmptyTest(JoinType type, bool parallel) {
auto l_schema = schema({field("l_i32", int32()), field("l_str", utf8())});
auto r_schema = schema({field("r_str", utf8()), field("r_i32", int32())});
int multiplicity = parallel ? 100 : 1;
BatchesWithSchema l_empty, r_empty, l_n_empty, r_n_empty;
l_empty = GenerateBatchesFromString(l_schema, {R"([])"}, multiplicity);
r_empty = GenerateBatchesFromString(r_schema, {R"([])"}, multiplicity);
l_n_empty =
GenerateBatchesFromString(l_schema, {R"([[0,"d"], [1,"b"]])"}, multiplicity);
r_n_empty = GenerateBatchesFromString(r_schema, {R"([["f", 0], ["b", 1], ["b", 2]])"},
multiplicity);
std::vector<FieldRef> l_keys{{"l_str"}};
std::vector<FieldRef> r_keys{{"r_str"}};
switch (type) {
case JoinType::LEFT_SEMI:
// both empty
CheckRunOutput(type, l_empty, r_empty, l_keys, r_keys, l_empty, parallel);
// right empty
CheckRunOutput(type, l_n_empty, r_empty, l_keys, r_keys, l_empty, parallel);
// left empty
CheckRunOutput(type, l_empty, r_n_empty, l_keys, r_keys, l_empty, parallel);
break;
case JoinType::RIGHT_SEMI:
// both empty
CheckRunOutput(type, l_empty, r_empty, l_keys, r_keys, r_empty, parallel);
// right empty
CheckRunOutput(type, l_n_empty, r_empty, l_keys, r_keys, r_empty, parallel);
// left empty
CheckRunOutput(type, l_empty, r_n_empty, l_keys, r_keys, r_empty, parallel);
break;
case JoinType::LEFT_ANTI:
// both empty
CheckRunOutput(type, l_empty, r_empty, l_keys, r_keys, l_empty, parallel);
// right empty
CheckRunOutput(type, l_n_empty, r_empty, l_keys, r_keys, l_n_empty, parallel);
// left empty
CheckRunOutput(type, l_empty, r_n_empty, l_keys, r_keys, l_empty, parallel);
break;
case JoinType::RIGHT_ANTI:
// both empty
CheckRunOutput(type, l_empty, r_empty, l_keys, r_keys, r_empty, parallel);
// right empty
CheckRunOutput(type, l_n_empty, r_empty, l_keys, r_keys, r_empty, parallel);
// left empty
CheckRunOutput(type, l_empty, r_n_empty, l_keys, r_keys, r_n_empty, parallel);
break;
case JoinType::INNER:
case JoinType::LEFT_OUTER:
case JoinType::RIGHT_OUTER:
case JoinType::FULL_OUTER:
default:
FAIL() << "join type not implemented!";
}
}
class HashJoinTest : public testing::TestWithParam<std::tuple<JoinType, bool>> {};
INSTANTIATE_TEST_SUITE_P(
HashJoinTest, HashJoinTest,
::testing::Combine(::testing::Values(JoinType::LEFT_SEMI, JoinType::RIGHT_SEMI,
JoinType::LEFT_ANTI, JoinType::RIGHT_ANTI),
::testing::Values(false, true)));
TEST_P(HashJoinTest, TestSemiJoins) {
RunNonEmptyTest(std::get<0>(GetParam()), std::get<1>(GetParam()));
}
TEST_P(HashJoinTest, TestSemiJoinsEmpty) {
RunEmptyTest(std::get<0>(GetParam()), std::get<1>(GetParam()));
}
class Random64Bit {
public:
explicit Random64Bit(random::SeedType seed) : rng_(seed) {}
uint64_t next() { return dist_(rng_); }
template <typename T>
inline T from_range(const T& min_val, const T& max_val) {
return static_cast<T>(min_val + (next() % (max_val - min_val + 1)));
}
private:
random::pcg32_fast rng_;
std::uniform_int_distribution<uint64_t> dist_;
};
struct RandomDataTypeConstraints {
int64_t data_type_enabled_mask;
// Null related
double min_null_probability;
double max_null_probability;
// Binary related
int min_binary_length;
int max_binary_length;
// String related
int min_string_length;
int max_string_length;
void Default() {
data_type_enabled_mask = kInt1 | kInt2 | kInt4 | kInt8 | kBool | kBinary | kString;
min_null_probability = 0.0;
max_null_probability = 0.2;
min_binary_length = 1;
max_binary_length = 40;
min_string_length = 0;
max_string_length = 40;
}
void OnlyInt(int int_size, bool allow_nulls) {
Default();
data_type_enabled_mask =
int_size == 8 ? kInt8 : int_size == 4 ? kInt4 : int_size == 2 ? kInt2 : kInt1;
if (!allow_nulls) {
max_null_probability = 0.0;
}
}
void OnlyString(bool allow_nulls) {
Default();
data_type_enabled_mask = kString;
if (!allow_nulls) {
max_null_probability = 0.0;
}
}
// Data type mask constants
static constexpr int64_t kInt1 = 1;
static constexpr int64_t kInt2 = 2;
static constexpr int64_t kInt4 = 4;
static constexpr int64_t kInt8 = 8;
static constexpr int64_t kBool = 16;
static constexpr int64_t kBinary = 32;
static constexpr int64_t kString = 64;
};
struct RandomDataType {
double null_probability;
bool is_fixed_length;
int fixed_length;
int min_string_length;
int max_string_length;
static RandomDataType Random(Random64Bit& rng,
const RandomDataTypeConstraints& constraints) {
RandomDataType result;
if ((constraints.data_type_enabled_mask & constraints.kString) != 0) {
if (constraints.data_type_enabled_mask != constraints.kString) {
// Both string and fixed length types enabled
// 50% chance of string
result.is_fixed_length = ((rng.next() % 2) == 0);
} else {
result.is_fixed_length = false;
}
} else {
result.is_fixed_length = true;
}
if (constraints.max_null_probability > 0.0) {
// 25% chance of no nulls
// Uniform distribution of null probability from min to max
result.null_probability = ((rng.next() % 4) == 0)
? 0.0
: static_cast<double>(rng.next() % 1025) / 1024.0 *
(constraints.max_null_probability -
constraints.min_null_probability) +
constraints.min_null_probability;
} else {
result.null_probability = 0.0;
}
// Pick data type for fixed length
if (result.is_fixed_length) {
int log_type;
for (;;) {
log_type = rng.next() % 6;
if (constraints.data_type_enabled_mask & (1ULL << log_type)) {
break;
}
}
if ((1ULL << log_type) == constraints.kBinary) {
for (;;) {
result.fixed_length = rng.from_range(constraints.min_binary_length,
constraints.max_binary_length);
if (result.fixed_length != 1 && result.fixed_length != 2 &&
result.fixed_length != 4 && result.fixed_length != 8) {
break;
}
}
} else {
result.fixed_length =
((1ULL << log_type) == constraints.kBool) ? 0 : (1ULL << log_type);
}
} else {
// Pick parameters for string
result.min_string_length =
rng.from_range(constraints.min_string_length, constraints.max_string_length);
result.max_string_length =
rng.from_range(constraints.min_string_length, constraints.max_string_length);
if (result.min_string_length > result.max_string_length) {
std::swap(result.min_string_length, result.max_string_length);
}
}
return result;
}
};
struct RandomDataTypeVector {
std::vector<RandomDataType> data_types;
void AddRandom(Random64Bit& rng, const RandomDataTypeConstraints& constraints) {
data_types.push_back(RandomDataType::Random(rng, constraints));
}
void Print() {
for (size_t i = 0; i < data_types.size(); ++i) {
if (!data_types[i].is_fixed_length) {
std::cout << "str[" << data_types[i].min_string_length << ".."
<< data_types[i].max_string_length << "]";
SCOPED_TRACE("str[" + std::to_string(data_types[i].min_string_length) + ".." +
std::to_string(data_types[i].max_string_length) + "]");
} else {
std::cout << "int[" << data_types[i].fixed_length << "]";
SCOPED_TRACE("int[" + std::to_string(data_types[i].fixed_length) + "]");
}
}
std::cout << std::endl;
}
};
std::vector<std::shared_ptr<Array>> GenRandomRecords(
Random64Bit& rng, const std::vector<RandomDataType>& data_types, int num_rows) {
std::vector<std::shared_ptr<Array>> result;
random::RandomArrayGenerator rag(static_cast<random::SeedType>(rng.next()));
for (size_t i = 0; i < data_types.size(); ++i) {
if (data_types[i].is_fixed_length) {
switch (data_types[i].fixed_length) {
case 0:
result.push_back(rag.Boolean(num_rows, 0.5, data_types[i].null_probability));
break;
case 1:
result.push_back(rag.UInt8(num_rows, std::numeric_limits<uint8_t>::min(),
std::numeric_limits<uint8_t>::max(),
data_types[i].null_probability));
break;
case 2:
result.push_back(rag.UInt16(num_rows, std::numeric_limits<uint16_t>::min(),
std::numeric_limits<uint16_t>::max(),
data_types[i].null_probability));
break;
case 4:
result.push_back(rag.UInt32(num_rows, std::numeric_limits<uint32_t>::min(),
std::numeric_limits<uint32_t>::max(),
data_types[i].null_probability));
break;
case 8:
result.push_back(rag.UInt64(num_rows, std::numeric_limits<uint64_t>::min(),
std::numeric_limits<uint64_t>::max(),
data_types[i].null_probability));
break;
default:
result.push_back(rag.FixedSizeBinary(num_rows, data_types[i].fixed_length,
data_types[i].null_probability));
break;
}
} else {
result.push_back(rag.String(num_rows, data_types[i].min_string_length,
data_types[i].max_string_length,
data_types[i].null_probability));
}
}
return result;
}
// Index < 0 means appending null values to all columns.
//
void TakeUsingVector(ExecContext* ctx, const std::vector<std::shared_ptr<Array>>& input,
const std::vector<int32_t> indices,
std::vector<std::shared_ptr<Array>>* result) {
ASSERT_OK_AND_ASSIGN(
std::shared_ptr<Buffer> buf,
AllocateBuffer(indices.size() * sizeof(int32_t), ctx->memory_pool()));
int32_t* buf_indices = reinterpret_cast<int32_t*>(buf->mutable_data());
bool has_null_rows = false;
for (size_t i = 0; i < indices.size(); ++i) {
if (indices[i] < 0) {
buf_indices[i] = 0;
has_null_rows = true;
} else {
buf_indices[i] = indices[i];
}
}
std::shared_ptr<Array> indices_array = MakeArray(ArrayData::Make(
int32(), indices.size(), {nullptr, std::move(buf)}, /*null_count=*/0));
result->resize(input.size());
for (size_t i = 0; i < result->size(); ++i) {
ASSERT_OK_AND_ASSIGN(Datum new_array, Take(input[i], indices_array));
(*result)[i] = new_array.make_array();
}
if (has_null_rows) {
for (size_t i = 0; i < result->size(); ++i) {
if ((*result)[i]->data()->buffers[0] == NULLPTR) {
ASSERT_OK_AND_ASSIGN(std::shared_ptr<Buffer> null_buf,
AllocateBitmap(indices.size(), ctx->memory_pool()));
uint8_t* non_nulls = null_buf->mutable_data();
memset(non_nulls, 0xFF, BitUtil::BytesForBits(indices.size()));
if ((*result)[i]->data()->buffers.size() == 2) {
(*result)[i] = MakeArray(
ArrayData::Make((*result)[i]->type(), indices.size(),
{std::move(null_buf), (*result)[i]->data()->buffers[1]}));
} else {
(*result)[i] = MakeArray(
ArrayData::Make((*result)[i]->type(), indices.size(),
{std::move(null_buf), (*result)[i]->data()->buffers[1],
(*result)[i]->data()->buffers[2]}));
}
}
(*result)[i]->data()->SetNullCount(kUnknownNullCount);
}
for (size_t i = 0; i < indices.size(); ++i) {
if (indices[i] < 0) {
for (size_t col = 0; col < result->size(); ++col) {
uint8_t* non_nulls = (*result)[col]->data()->buffers[0]->mutable_data();
BitUtil::ClearBit(non_nulls, i);
}
}
}
}
}
// Generate random arrays given list of data type descriptions and null probabilities.
// Make sure that all generated records are unique.
// The actual number of generated records may be lower than desired because duplicates
// will be removed without replacement.
//
std::vector<std::shared_ptr<Array>> GenRandomUniqueRecords(
Random64Bit& rng, const RandomDataTypeVector& data_types, int num_desired,
int* num_actual) {
std::vector<std::shared_ptr<Array>> result =
GenRandomRecords(rng, data_types.data_types, num_desired);
ExecContext* ctx = default_exec_context();
std::vector<ValueDescr> val_descrs;
for (size_t i = 0; i < result.size(); ++i) {
val_descrs.push_back(ValueDescr(result[i]->type(), ValueDescr::ARRAY));
}
internal::RowEncoder encoder;
encoder.Init(val_descrs, ctx);
ExecBatch batch({}, num_desired);
batch.values.resize(result.size());
for (size_t i = 0; i < result.size(); ++i) {
batch.values[i] = result[i];
}
Status status = encoder.EncodeAndAppend(batch);
ARROW_DCHECK(status.ok());
std::unordered_map<std::string, int> uniques;
std::vector<int32_t> ids;
for (int i = 0; i < num_desired; ++i) {
if (uniques.find(encoder.encoded_row(i)) == uniques.end()) {
uniques.insert(std::make_pair(encoder.encoded_row(i), i));
ids.push_back(i);
}
}
*num_actual = static_cast<int>(uniques.size());
std::vector<std::shared_ptr<Array>> output;
TakeUsingVector(ctx, result, ids, &output);
return output;
}
std::vector<bool> NullInKey(const std::vector<JoinKeyCmp>& cmp,
const std::vector<std::shared_ptr<Array>>& key) {
ARROW_DCHECK(cmp.size() <= key.size());
ARROW_DCHECK(key.size() > 0);
std::vector<bool> result;
result.resize(key[0]->length());
for (size_t i = 0; i < result.size(); ++i) {
result[i] = false;
}
for (size_t i = 0; i < cmp.size(); ++i) {
if (cmp[i] != JoinKeyCmp::EQ) {
continue;
}
if (key[i]->data()->buffers[0] == NULLPTR) {
continue;
}
const uint8_t* nulls = key[i]->data()->buffers[0]->data();
if (!nulls) {
continue;
}
for (size_t j = 0; j < result.size(); ++j) {
if (!BitUtil::GetBit(nulls, j)) {
result[j] = true;
}
}
}
return result;
}
void GenRandomJoinTables(ExecContext* ctx, Random64Bit& rng, int num_rows_l,
int num_rows_r, int num_keys_common, int num_keys_left,
int num_keys_right, const RandomDataTypeVector& key_types,
const RandomDataTypeVector& payload_left_types,
const RandomDataTypeVector& payload_right_types,
std::vector<int32_t>* key_id_l, std::vector<int32_t>* key_id_r,
std::vector<std::shared_ptr<Array>>* left,
std::vector<std::shared_ptr<Array>>* right) {
// Generate random keys dictionary
//
int num_keys_desired = num_keys_left + num_keys_right - num_keys_common;
int num_keys_actual = 0;
std::vector<std::shared_ptr<Array>> keys =
GenRandomUniqueRecords(rng, key_types, num_keys_desired, &num_keys_actual);
// There will be three dictionary id ranges:
// - common keys [0..num_keys_common-1]
// - keys on right that are not on left [num_keys_common..num_keys_right-1]
// - keys on left that are not on right [num_keys_right..num_keys_actual-1]
//
num_keys_common = static_cast<int>(static_cast<int64_t>(num_keys_common) *
num_keys_actual / num_keys_desired);
num_keys_right = static_cast<int>(static_cast<int64_t>(num_keys_right) *
num_keys_actual / num_keys_desired);
ARROW_DCHECK(num_keys_right >= num_keys_common);
num_keys_left = num_keys_actual - num_keys_right + num_keys_common;
if (num_keys_left == 0) {
ARROW_DCHECK(num_keys_common == 0 && num_keys_right > 0);
++num_keys_left;
++num_keys_common;
}
if (num_keys_right == 0) {
ARROW_DCHECK(num_keys_common == 0 && num_keys_left > 0);
++num_keys_right;
++num_keys_common;
}
ARROW_DCHECK(num_keys_left >= num_keys_common);
ARROW_DCHECK(num_keys_left + num_keys_right - num_keys_common == num_keys_actual);
key_id_l->resize(num_rows_l);
for (int i = 0; i < num_rows_l; ++i) {
(*key_id_l)[i] = rng.from_range(0, num_keys_left - 1);
if ((*key_id_l)[i] >= num_keys_common) {
(*key_id_l)[i] += num_keys_right - num_keys_common;
}
}
key_id_r->resize(num_rows_r);
for (int i = 0; i < num_rows_r; ++i) {
(*key_id_r)[i] = rng.from_range(0, num_keys_right - 1);
}
std::vector<std::shared_ptr<Array>> key_l;
std::vector<std::shared_ptr<Array>> key_r;
TakeUsingVector(ctx, keys, *key_id_l, &key_l);
TakeUsingVector(ctx, keys, *key_id_r, &key_r);
std::vector<std::shared_ptr<Array>> payload_l =
GenRandomRecords(rng, payload_left_types.data_types, num_rows_l);
std::vector<std::shared_ptr<Array>> payload_r =
GenRandomRecords(rng, payload_right_types.data_types, num_rows_r);
left->resize(key_l.size() + payload_l.size());
for (size_t i = 0; i < key_l.size(); ++i) {
(*left)[i] = key_l[i];
}
for (size_t i = 0; i < payload_l.size(); ++i) {
(*left)[key_l.size() + i] = payload_l[i];
}
right->resize(key_r.size() + payload_r.size());
for (size_t i = 0; i < key_r.size(); ++i) {
(*right)[i] = key_r[i];
}
for (size_t i = 0; i < payload_r.size(); ++i) {
(*right)[key_r.size() + i] = payload_r[i];
}
}
std::vector<std::shared_ptr<Array>> ConstructJoinOutputFromRowIds(
ExecContext* ctx, const std::vector<int32_t>& row_ids_l,
const std::vector<int32_t>& row_ids_r, const std::vector<std::shared_ptr<Array>>& l,
const std::vector<std::shared_ptr<Array>>& r,
const std::vector<int>& shuffle_output_l, const std::vector<int>& shuffle_output_r) {
std::vector<std::shared_ptr<Array>> full_output_l;
std::vector<std::shared_ptr<Array>> full_output_r;
TakeUsingVector(ctx, l, row_ids_l, &full_output_l);
TakeUsingVector(ctx, r, row_ids_r, &full_output_r);
std::vector<std::shared_ptr<Array>> result;
result.resize(shuffle_output_l.size() + shuffle_output_r.size());
for (size_t i = 0; i < shuffle_output_l.size(); ++i) {
result[i] = full_output_l[shuffle_output_l[i]];
}
for (size_t i = 0; i < shuffle_output_r.size(); ++i) {
result[shuffle_output_l.size() + i] = full_output_r[shuffle_output_r[i]];
}
return result;
}
BatchesWithSchema TableToBatches(Random64Bit& rng, int num_batches,
const std::vector<std::shared_ptr<Array>>& table,
const std::string& column_name_prefix) {
BatchesWithSchema result;
std::vector<std::shared_ptr<Field>> fields;
fields.resize(table.size());
for (size_t i = 0; i < table.size(); ++i) {
fields[i] = std::make_shared<Field>(column_name_prefix + std::to_string(i),
table[i]->type(), true);
}
result.schema = std::make_shared<Schema>(std::move(fields));
int64_t length = table[0]->length();
num_batches = std::min(num_batches, static_cast<int>(length));
std::vector<int64_t> batch_offsets;
batch_offsets.push_back(0);
batch_offsets.push_back(length);
std::unordered_set<int64_t> batch_offset_set;
for (int i = 0; i < num_batches - 1; ++i) {
for (;;) {
int64_t offset = rng.from_range(static_cast<int64_t>(1), length - 1);
if (batch_offset_set.find(offset) == batch_offset_set.end()) {
batch_offset_set.insert(offset);
batch_offsets.push_back(offset);
break;
}
}
}
std::sort(batch_offsets.begin(), batch_offsets.end());
for (int i = 0; i < num_batches; ++i) {
int64_t batch_offset = batch_offsets[i];
int64_t batch_length = batch_offsets[i + 1] - batch_offsets[i];
ExecBatch batch({}, batch_length);
batch.values.resize(table.size());
for (size_t col = 0; col < table.size(); ++col) {
batch.values[col] = table[col]->data()->Slice(batch_offset, batch_length);
}
result.batches.push_back(batch);
}
return result;
}
// -1 in result means outputting all corresponding fields as nulls
//
void HashJoinSimpleInt(JoinType join_type, const std::vector<int32_t>& l,
const std::vector<bool>& null_in_key_l,
const std::vector<int32_t>& r,
const std::vector<bool>& null_in_key_r,
std::vector<int32_t>* result_l, std::vector<int32_t>* result_r,
int64_t output_length_limit, bool* length_limit_reached) {
*length_limit_reached = false;
bool switch_sides = false;
switch (join_type) {
case JoinType::RIGHT_SEMI:
join_type = JoinType::LEFT_SEMI;
switch_sides = true;
break;
case JoinType::RIGHT_ANTI:
join_type = JoinType::LEFT_ANTI;
switch_sides = true;
break;
case JoinType::RIGHT_OUTER:
join_type = JoinType::LEFT_OUTER;
switch_sides = true;
break;
default:
break;
}
const std::vector<int32_t>& build = switch_sides ? l : r;
const std::vector<int32_t>& probe = switch_sides ? r : l;
const std::vector<bool>& null_in_key_build =
switch_sides ? null_in_key_l : null_in_key_r;
const std::vector<bool>& null_in_key_probe =
switch_sides ? null_in_key_r : null_in_key_l;
std::vector<int32_t>* result_build = switch_sides ? result_l : result_r;
std::vector<int32_t>* result_probe = switch_sides ? result_r : result_l;
std::unordered_multimap<int64_t, int64_t> map_build;
for (size_t i = 0; i < build.size(); ++i) {
map_build.insert(std::make_pair(build[i], i));
}
std::vector<bool> match_build;
match_build.resize(build.size());
for (size_t i = 0; i < build.size(); ++i) {
match_build[i] = false;
}
for (int32_t i = 0; i < static_cast<int32_t>(probe.size()); ++i) {
std::vector<int32_t> match_probe;
if (!null_in_key_probe[i]) {
auto range = map_build.equal_range(probe[i]);
for (auto it = range.first; it != range.second; ++it) {
if (!null_in_key_build[it->second]) {
match_probe.push_back(static_cast<int32_t>(it->second));
match_build[it->second] = true;
}
}
}
switch (join_type) {
case JoinType::LEFT_SEMI:
if (!match_probe.empty()) {
result_probe->push_back(i);
result_build->push_back(-1);
}
break;
case JoinType::LEFT_ANTI:
if (match_probe.empty()) {
result_probe->push_back(i);
result_build->push_back(-1);
}
break;
case JoinType::INNER:
for (size_t j = 0; j < match_probe.size(); ++j) {
result_probe->push_back(i);
result_build->push_back(match_probe[j]);
}
break;
case JoinType::LEFT_OUTER:
case JoinType::FULL_OUTER:
if (match_probe.empty()) {
result_probe->push_back(i);
result_build->push_back(-1);
} else {
for (size_t j = 0; j < match_probe.size(); ++j) {
result_probe->push_back(i);
result_build->push_back(match_probe[j]);
}
}
break;
default:
ARROW_DCHECK(false);
break;
}
if (static_cast<int64_t>(result_probe->size()) >= output_length_limit) {
*length_limit_reached = true;
return;
}
}
if (join_type == JoinType::FULL_OUTER) {
for (int32_t i = 0; i < static_cast<int32_t>(build.size()); ++i) {
if (!match_build[i]) {
result_probe->push_back(-1);
result_build->push_back(i);
}
}
}
}
std::vector<int> GenShuffle(Random64Bit& rng, int length) {
std::vector<int> shuffle(length);
std::iota(shuffle.begin(), shuffle.end(), 0);
for (int i = 0; i < length * 2; ++i) {
int from = rng.from_range(0, length - 1);
int to = rng.from_range(0, length - 1);
if (from != to) {
std::swap(shuffle[from], shuffle[to]);
}
}
return shuffle;
}
void GenJoinFieldRefs(Random64Bit& rng, int num_key_fields, bool no_output,
const std::vector<std::shared_ptr<Array>>& original_input,
const std::string& field_name_prefix,
std::vector<std::shared_ptr<Array>>* new_input,
std::vector<FieldRef>* keys, std::vector<FieldRef>* output,
std::vector<int>* output_field_ids) {
// Permute input
std::vector<int> shuffle = GenShuffle(rng, static_cast<int>(original_input.size()));
new_input->resize(original_input.size());
for (size_t i = 0; i < original_input.size(); ++i) {
(*new_input)[i] = original_input[shuffle[i]];
}
// Compute key field refs
keys->resize(num_key_fields);
for (size_t i = 0; i < shuffle.size(); ++i) {
if (shuffle[i] < num_key_fields) {
bool use_by_name_ref = (rng.from_range(0, 1) == 0);
if (use_by_name_ref) {
(*keys)[shuffle[i]] = FieldRef(field_name_prefix + std::to_string(i));
} else {
(*keys)[shuffle[i]] = FieldRef(static_cast<int>(i));
}
}
}
// Compute output field refs
if (!no_output) {
int num_output = rng.from_range(1, static_cast<int>(original_input.size() + 1));
output_field_ids->resize(num_output);
output->resize(num_output);
for (int i = 0; i < num_output; ++i) {
int col_id = rng.from_range(0, static_cast<int>(original_input.size() - 1));
(*output_field_ids)[i] = col_id;
(*output)[i] = (rng.from_range(0, 1) == 0)
? FieldRef(field_name_prefix + std::to_string(col_id))
: FieldRef(col_id);
}
}
}
std::shared_ptr<Table> HashJoinSimple(
ExecContext* ctx, JoinType join_type, const std::vector<JoinKeyCmp>& cmp,
int num_key_fields, const std::vector<int32_t>& key_id_l,
const std::vector<int32_t>& key_id_r,
const std::vector<std::shared_ptr<Array>>& original_l,
const std::vector<std::shared_ptr<Array>>& original_r,
const std::vector<std::shared_ptr<Array>>& l,
const std::vector<std::shared_ptr<Array>>& r, const std::vector<int>& output_ids_l,
const std::vector<int>& output_ids_r, int64_t output_length_limit,
bool* length_limit_reached) {
std::vector<std::shared_ptr<Array>> key_l(num_key_fields);
std::vector<std::shared_ptr<Array>> key_r(num_key_fields);
for (int i = 0; i < num_key_fields; ++i) {
key_l[i] = original_l[i];
key_r[i] = original_r[i];
}
std::vector<bool> null_key_l = NullInKey(cmp, key_l);
std::vector<bool> null_key_r = NullInKey(cmp, key_r);
std::vector<int32_t> row_ids_l;
std::vector<int32_t> row_ids_r;
HashJoinSimpleInt(join_type, key_id_l, null_key_l, key_id_r, null_key_r, &row_ids_l,
&row_ids_r, output_length_limit, length_limit_reached);
std::vector<std::shared_ptr<Array>> result = ConstructJoinOutputFromRowIds(
ctx, row_ids_l, row_ids_r, l, r, output_ids_l, output_ids_r);
std::vector<std::shared_ptr<Field>> fields(result.size());
for (size_t i = 0; i < result.size(); ++i) {
fields[i] = std::make_shared<Field>("a" + std::to_string(i), result[i]->type(), true);
}
std::shared_ptr<Schema> schema = std::make_shared<Schema>(std::move(fields));
return Table::Make(schema, result, result[0]->length());
}
void HashJoinWithExecPlan(Random64Bit& rng, bool parallel,
const HashJoinNodeOptions& join_options,
const std::shared_ptr<Schema>& output_schema,
const std::vector<std::shared_ptr<Array>>& l,
const std::vector<std::shared_ptr<Array>>& r, int num_batches_l,
int num_batches_r, std::shared_ptr<Table>* output) {
auto exec_ctx = arrow::internal::make_unique<ExecContext>(
default_memory_pool(), parallel ? arrow::internal::GetCpuThreadPool() : nullptr);
ASSERT_OK_AND_ASSIGN(auto plan, ExecPlan::Make(exec_ctx.get()));
// add left source
BatchesWithSchema l_batches = TableToBatches(rng, num_batches_l, l, "l_");
ASSERT_OK_AND_ASSIGN(
ExecNode * l_source,
MakeExecNode("source", plan.get(), {},
SourceNodeOptions{l_batches.schema, l_batches.gen(parallel,
/*slow=*/false)}));
// add right source
BatchesWithSchema r_batches = TableToBatches(rng, num_batches_r, r, "r_");
ASSERT_OK_AND_ASSIGN(
ExecNode * r_source,
MakeExecNode("source", plan.get(), {},
SourceNodeOptions{r_batches.schema, r_batches.gen(parallel,
/*slow=*/false)}));
ASSERT_OK_AND_ASSIGN(ExecNode * join, MakeExecNode("hashjoin", plan.get(),
{l_source, r_source}, join_options));
AsyncGenerator<util::optional<ExecBatch>> sink_gen;
ASSERT_OK_AND_ASSIGN(
std::ignore, MakeExecNode("sink", plan.get(), {join}, SinkNodeOptions{&sink_gen}));
ASSERT_FINISHES_OK_AND_ASSIGN(auto res, StartAndCollect(plan.get(), sink_gen));
ASSERT_OK_AND_ASSIGN(*output, TableFromExecBatches(output_schema, res));
}
TEST(HashJoin, Random) {
Random64Bit rng(42);
int num_tests = 100;
for (int test_id = 0; test_id < num_tests; ++test_id) {
bool parallel = (rng.from_range(0, 1) == 1);
auto exec_ctx = arrow::internal::make_unique<ExecContext>(
default_memory_pool(), parallel ? arrow::internal::GetCpuThreadPool() : nullptr);
// Constraints
RandomDataTypeConstraints type_constraints;
type_constraints.Default();
// type_constraints.OnlyInt(1, true);
constexpr int max_num_key_fields = 3;
constexpr int max_num_payload_fields = 3;
const char* join_type_names[] = {"LEFT_SEMI", "RIGHT_SEMI", "LEFT_ANTI",
"RIGHT_ANTI", "INNER", "LEFT_OUTER",
"RIGHT_OUTER", "FULL_OUTER"};
std::vector<JoinType> join_type_options{JoinType::LEFT_SEMI, JoinType::RIGHT_SEMI,
JoinType::LEFT_ANTI, JoinType::RIGHT_ANTI,
JoinType::INNER, JoinType::LEFT_OUTER,
JoinType::RIGHT_OUTER, JoinType::FULL_OUTER};
constexpr int join_type_mask = 0xFF;
// for INNER join only:
// constexpr int join_type_mask = 0x10;
std::vector<JoinKeyCmp> key_cmp_options{JoinKeyCmp::EQ, JoinKeyCmp::IS};
constexpr int key_cmp_mask = 0x03;
// for EQ only:
// constexpr int key_cmp_mask = 0x01;
constexpr int min_num_rows = 1;
const int max_num_rows = parallel ? 20000 : 2000;
constexpr int min_batch_size = 10;
constexpr int max_batch_size = 100;
// Generate list of key field data types
int num_key_fields = rng.from_range(1, max_num_key_fields);
RandomDataTypeVector key_types;
for (int i = 0; i < num_key_fields; ++i) {
key_types.AddRandom(rng, type_constraints);
}
// Generate lists of payload data types
int num_payload_fields[2];
RandomDataTypeVector payload_types[2];
for (int i = 0; i < 2; ++i) {
num_payload_fields[i] = rng.from_range(0, max_num_payload_fields);
for (int j = 0; j < num_payload_fields[i]; ++j) {
payload_types[i].AddRandom(rng, type_constraints);
}