wgtmac commented on code in PR #36779:
URL: https://github.com/apache/arrow/pull/36779#discussion_r1268958773
##########
cpp/src/parquet/arrow/reader.h:
##########
@@ -249,6 +249,90 @@ class PARQUET_EXPORT FileReader {
virtual ::arrow::Status ReadRowGroups(const std::vector<int>& row_groups,
std::shared_ptr<::arrow::Table>* out)
= 0;
+ using AsyncBatchGenerator =
+ std::function<::arrow::Future<std::shared_ptr<::arrow::RecordBatch>>()>;
+
+ /// \brief Read a single row group from the file
+ ///
+ /// \see ReadRowGroupsAsync for operation details
+ ///
+ /// \param i the index of the row group to read
+ /// \param cpu_executor an executor to use to run CPU tasks
+ /// \param allow_sliced_batches if false, an error is raised if a batch has
too much
+ /// data for the given batch size. If true,
smaller
+ /// batches will be returned instead.
+ virtual AsyncBatchGenerator ReadRowGroupAsync(int i,
+ ::arrow::internal::Executor*
cpu_executor,
+ bool allow_sliced_batches =
false) = 0;
+ /// \brief Read some columns from a single row group from the file
+ ///
+ /// \see ReadRowGroupsAsync for operation details
+ /// \see ReadTable for details on how column indices are resolved
+ ///
+ /// \param i the index of the row group to read
+ /// \param column_indices leaf-indices of the columns to read
+ /// \param cpu_executor an executor to use to run CPU tasks
+ /// \param allow_sliced_batches if false, an error is raised if a batch has
too much
+ /// data for the given batch size. If true,
smaller
+ /// batches will be returned instead.
+ virtual AsyncBatchGenerator ReadRowGroupAsync(int i,
+ const std::vector<int>&
column_indices,
+ ::arrow::internal::Executor*
cpu_executor,
+ bool allow_sliced_batches =
false) = 0;
+
+ /// \brief Read row groups from the file
+ ///
+ /// \see ReadRowGroupsAsync for operation details
+ ///
+ /// \param row_groups indices of the row groups to read
+ /// \param cpu_executor an executor to use to run CPU tasks
+ /// \param allow_sliced_batches if false, an error is raised if a batch has
too much
Review Comment:
In which case sliced batches is a concern?
##########
cpp/src/parquet/arrow/reader.h:
##########
@@ -249,6 +249,90 @@ class PARQUET_EXPORT FileReader {
virtual ::arrow::Status ReadRowGroups(const std::vector<int>& row_groups,
std::shared_ptr<::arrow::Table>* out)
= 0;
+ using AsyncBatchGenerator =
+ std::function<::arrow::Future<std::shared_ptr<::arrow::RecordBatch>>()>;
+
+ /// \brief Read a single row group from the file
+ ///
+ /// \see ReadRowGroupsAsync for operation details
+ ///
+ /// \param i the index of the row group to read
+ /// \param cpu_executor an executor to use to run CPU tasks
+ /// \param allow_sliced_batches if false, an error is raised if a batch has
too much
+ /// data for the given batch size. If true,
smaller
+ /// batches will be returned instead.
+ virtual AsyncBatchGenerator ReadRowGroupAsync(int i,
+ ::arrow::internal::Executor*
cpu_executor,
+ bool allow_sliced_batches =
false) = 0;
+ /// \brief Read some columns from a single row group from the file
+ ///
+ /// \see ReadRowGroupsAsync for operation details
+ /// \see ReadTable for details on how column indices are resolved
+ ///
+ /// \param i the index of the row group to read
+ /// \param column_indices leaf-indices of the columns to read
+ /// \param cpu_executor an executor to use to run CPU tasks
+ /// \param allow_sliced_batches if false, an error is raised if a batch has
too much
+ /// data for the given batch size. If true,
smaller
+ /// batches will be returned instead.
+ virtual AsyncBatchGenerator ReadRowGroupAsync(int i,
+ const std::vector<int>&
column_indices,
+ ::arrow::internal::Executor*
cpu_executor,
+ bool allow_sliced_batches =
false) = 0;
+
+ /// \brief Read row groups from the file
+ ///
+ /// \see ReadRowGroupsAsync for operation details
+ ///
+ /// \param row_groups indices of the row groups to read
+ /// \param cpu_executor an executor to use to run CPU tasks
+ /// \param allow_sliced_batches if false, an error is raised if a batch has
too much
+ /// data for the given batch size. If true,
smaller
+ /// batches will be returned instead.
+ virtual AsyncBatchGenerator ReadRowGroupsAsync(
+ const std::vector<int>& row_groups, ::arrow::internal::Executor*
cpu_executor,
+ bool allow_sliced_batches = false) = 0;
+
+ /// \brief Read some columns from the given rows groups from the file
+ ///
+ /// If pre-buffering is enabled then all of the data will be read using the
pre-buffer
+ /// cache. See ParquetFileReader::PreBuffer for details on how this affects
memory and
+ /// performance.
+ ///
+ /// This operation is not perfectly async. The read from disk will be done
on an I/O
+ /// thread, which is correct. However, compression and column decoding is
also done on
+ /// the I/O thread which may not be ideal. The stage after that
(transferring the
+ /// decoded data into Arrow structures and fulfilling the future) should be
done as a
+ /// new task on the cpu_executor.
+ ///
+ /// The returned generator will respect the batch size set in the reader
properties.
+ /// Batches will not be larger than the given batch size. However, batches
may be
+ /// smaller. This can happen, for example, when there is not enough data or
when a
+ /// string column is too large to fit into a single batch. The parameter
+ /// `allow_sliced_batches` can be set to false to disallow this later case.
This can be
+ /// useful when you need to know exactly how many batches you will get from
the
+ /// operation before you start.
+ ///
+ /// Note: When reading multiple row groups there is no guarantee you will
get one
+ /// record batch per row group. Data from multiple row groups could get
combined into
+ /// a single batch.
+ ///
+ /// Note: If a row group has 0 rows it will effectively be ignored. If you
are only
+ /// reading empty row groups then the returned generated will immediately
finish. This
Review Comment:
```suggestion
/// reading empty row groups then the returned generator will immediately
finish. This
```
##########
cpp/src/parquet/arrow/arrow_reader_writer_test.cc:
##########
@@ -2514,6 +2517,137 @@ TEST(TestArrowReadWrite, GetRecordBatchGenerator) {
}
}
+TEST(TestArrowReadWrite, ReadRowGroupsAsync) {
+ constexpr int kNumRows = 1024;
+ constexpr int kRowGroupSize = 512;
+ constexpr int kNumColumns = 2;
+
+ std::shared_ptr<Table> table;
+ ASSERT_NO_FATAL_FAILURE(MakeDoubleTable(kNumColumns, kNumRows, 1, &table));
+
+ std::shared_ptr<Buffer> buffer;
+ ASSERT_NO_FATAL_FAILURE(WriteTableToBuffer(table, kRowGroupSize,
+
default_arrow_writer_properties(), &buffer));
+
+ for (std::vector<int> row_groups : std::vector<std::vector<int>>{{}, {0},
{0, 1}}) {
+ ARROW_SCOPED_TRACE("# row_groups = ", row_groups.size());
+ int32_t expected_total_rows = static_cast<int32_t>(row_groups.size()) *
kRowGroupSize;
+
+ for (std::vector<int> columns : std::vector<std::vector<int>>{{}, {0}, {0,
1}}) {
+ ARROW_SCOPED_TRACE("# columns = ", columns.size());
+
+ for (int row_group_size : {128, 512, 1024, 2048}) {
+ ARROW_SCOPED_TRACE("row_group_size = ", row_group_size);
+
+ ArrowReaderProperties properties = default_arrow_reader_properties();
+ properties.set_batch_size(row_group_size);
+ std::unique_ptr<FileReader> unique_reader;
+ FileReaderBuilder builder;
+ ASSERT_OK(builder.Open(std::make_shared<BufferReader>(buffer)));
+ ASSERT_OK(builder.properties(properties)->Build(&unique_reader));
+ auto batch_generator = unique_reader->ReadRowGroupsAsync(
+ row_groups, columns, ::arrow::internal::GetCpuThreadPool());
+
+ int64_t num_expected_batches =
Review Comment:
Just curious, is a predicable num_expected_batches useful in real case?
##########
cpp/src/parquet/arrow/reader.cc:
##########
@@ -1233,6 +1274,123 @@ Status FileReaderImpl::ReadRowGroups(const
std::vector<int>& row_groups,
return Status::OK();
}
+struct AsyncBatchGeneratorState {
+ ::arrow::internal::Executor* io_executor;
+ ::arrow::internal::Executor* cpu_executor;
+ std::vector<std::shared_ptr<ColumnReaderImpl>> column_readers;
+ std::queue<std::shared_ptr<RecordBatch>> overflow;
+ std::shared_ptr<::arrow::Schema> schema;
+ int64_t batch_size;
+ int64_t rows_remaining;
+ bool use_threads;
+ bool allow_sliced_batches;
+};
+
+class AsyncBatchGeneratorImpl {
+ public:
+ explicit AsyncBatchGeneratorImpl(std::shared_ptr<AsyncBatchGeneratorState>
state)
+ : state_(std::move(state)) {}
+ Future<std::shared_ptr<RecordBatch>> operator()() {
+ if (!state_->overflow.empty()) {
+ std::shared_ptr<RecordBatch> next = std::move(state_->overflow.front());
+ state_->overflow.pop();
+ return next;
+ }
+
+ if (state_->rows_remaining == 0) {
+ // Exhausted
+ return Future<std::shared_ptr<RecordBatch>>::MakeFinished(
+ ::arrow::IterationEnd<std::shared_ptr<RecordBatch>>());
+ }
+
+ int64_t rows_in_batch = std::min(state_->rows_remaining,
state_->batch_size);
+ state_->rows_remaining -= rows_in_batch;
+
+ // We read the columns in parallel. Each reader returns a chunked array.
This is
+ // because we might need to chunk a column if that column is too large. We
+ // do provide a batch size but even for a small batch size it is possible
that a
+ // column has extremely large strings which don't fit in a single batch.
+ Future<std::vector<std::shared_ptr<ChunkedArray>>> chunked_arrays_fut =
+ ::arrow::internal::OptionalParallelForAsync(
+ state_->use_threads, state_->column_readers,
+ [rows_in_batch](std::size_t, std::shared_ptr<ColumnReaderImpl>
column_reader)
+ -> Result<std::shared_ptr<ChunkedArray>> {
+ std::shared_ptr<ChunkedArray> chunked_array;
+ ARROW_RETURN_NOT_OK(
+ column_reader->NextBatch(rows_in_batch, &chunked_array));
+ return chunked_array;
+ });
+
+ // Grab the first batch of data and return it. If there is more than one
batch then
+ // throw the reamining batches into overflow and they will be fetched on
the next call
+ return chunked_arrays_fut.Then(
+ [state = state_,
+ rows_in_batch](const std::vector<std::shared_ptr<ChunkedArray>>&
chunks)
+ -> Result<std::shared_ptr<RecordBatch>> {
+ std::shared_ptr<Table> table =
+ Table::Make(state->schema, chunks, rows_in_batch);
+ ::arrow::TableBatchReader batch_reader(*table);
Review Comment:
Is there a handy way to directly convert ChunkedArray to RecordBatch? I am
not sure if going through a TableBatchReader is heavy or not.
##########
cpp/src/parquet/arrow/reader.cc:
##########
@@ -1233,6 +1274,123 @@ Status FileReaderImpl::ReadRowGroups(const
std::vector<int>& row_groups,
return Status::OK();
}
+struct AsyncBatchGeneratorState {
+ ::arrow::internal::Executor* io_executor;
+ ::arrow::internal::Executor* cpu_executor;
+ std::vector<std::shared_ptr<ColumnReaderImpl>> column_readers;
+ std::queue<std::shared_ptr<RecordBatch>> overflow;
+ std::shared_ptr<::arrow::Schema> schema;
+ int64_t batch_size;
+ int64_t rows_remaining;
+ bool use_threads;
+ bool allow_sliced_batches;
+};
+
+class AsyncBatchGeneratorImpl {
+ public:
+ explicit AsyncBatchGeneratorImpl(std::shared_ptr<AsyncBatchGeneratorState>
state)
+ : state_(std::move(state)) {}
+ Future<std::shared_ptr<RecordBatch>> operator()() {
+ if (!state_->overflow.empty()) {
+ std::shared_ptr<RecordBatch> next = std::move(state_->overflow.front());
+ state_->overflow.pop();
+ return next;
+ }
+
+ if (state_->rows_remaining == 0) {
+ // Exhausted
+ return Future<std::shared_ptr<RecordBatch>>::MakeFinished(
+ ::arrow::IterationEnd<std::shared_ptr<RecordBatch>>());
+ }
+
+ int64_t rows_in_batch = std::min(state_->rows_remaining,
state_->batch_size);
+ state_->rows_remaining -= rows_in_batch;
+
+ // We read the columns in parallel. Each reader returns a chunked array.
This is
+ // because we might need to chunk a column if that column is too large. We
+ // do provide a batch size but even for a small batch size it is possible
that a
+ // column has extremely large strings which don't fit in a single batch.
+ Future<std::vector<std::shared_ptr<ChunkedArray>>> chunked_arrays_fut =
+ ::arrow::internal::OptionalParallelForAsync(
Review Comment:
The `cpu_executor` is not used here.
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