/usr/local/lib64/python3.6/site-packages/pyarrow/include/arrow/dataset
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api.h11810644editdlrm
dataset.h101530644editdlrm
dataset_writer.h41730644editdlrm
discovery.h110170644editdlrm
file_base.h165550644editdlrm
file_csv.h40980644editdlrm
file_ipc.h41880644editdlrm
file_orc.h27180644editdlrm
file_parquet.h158100644editdlrm
partition.h145110644editdlrm
pch.h11940644editdlrm
plan.h11810644editdlrm
projector.h11350644editdlrm
scanner.h186660644editdlrm
test_util.h507350644editdlrm
type_fwd.h29540644editdlrm
visibility.h15280644editdlrm
Edit: /usr/local/lib64/python3.6/site-packages/pyarrow/include/arrow/dataset/scanner.h (18666B)
// 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. // This API is EXPERIMENTAL. #pragma once #include #include #include #include #include #include "arrow/compute/exec/expression.h" #include "arrow/compute/exec/options.h" #include "arrow/compute/type_fwd.h" #include "arrow/dataset/dataset.h" #include "arrow/dataset/projector.h" #include "arrow/dataset/type_fwd.h" #include "arrow/dataset/visibility.h" #include "arrow/io/interfaces.h" #include "arrow/memory_pool.h" #include "arrow/type_fwd.h" #include "arrow/util/async_generator.h" #include "arrow/util/iterator.h" #include "arrow/util/thread_pool.h" #include "arrow/util/type_fwd.h" namespace arrow { using RecordBatchGenerator = std::function>()>; namespace dataset { /// \defgroup dataset-scanning Scanning API /// /// @{ constexpr int64_t kDefaultBatchSize = 1 << 20; constexpr int32_t kDefaultBatchReadahead = 32; constexpr int32_t kDefaultFragmentReadahead = 8; constexpr int32_t kDefaultBackpressureHigh = 64; constexpr int32_t kDefaultBackpressureLow = 32; /// Scan-specific options, which can be changed between scans of the same dataset. struct ARROW_DS_EXPORT ScanOptions { /// A row filter (which will be pushed down to partitioning/reading if supported). compute::Expression filter = compute::literal(true); /// A projection expression (which can add/remove/rename columns). compute::Expression projection; /// Schema with which batches will be read from fragments. This is also known as the /// "reader schema" it will be used (for example) in constructing CSV file readers to /// identify column types for parsing. Usually only a subset of its fields (see /// MaterializedFields) will be materialized during a scan. std::shared_ptr dataset_schema; /// Schema of projected record batches. This is independent of dataset_schema as its /// fields are derived from the projection. For example, let /// /// dataset_schema = {"a": int32, "b": int32, "id": utf8} /// projection = project({equal(field_ref("a"), field_ref("b"))}, {"a_plus_b"}) /// /// (no filter specified). In this case, the projected_schema would be /// /// {"a_plus_b": int32} std::shared_ptr projected_schema; /// Maximum row count for scanned batches. int64_t batch_size = kDefaultBatchSize; /// How many batches to read ahead within a file /// /// Set to 0 to disable batch readahead /// /// Note: May not be supported by all formats /// Note: May not be supported by all scanners /// Note: Will be ignored if use_threads is set to false int32_t batch_readahead = kDefaultBatchReadahead; /// How many files to read ahead /// /// Set to 0 to disable fragment readahead /// /// Note: May not be enforced by all scanners /// Note: Will be ignored if use_threads is set to false int32_t fragment_readahead = kDefaultFragmentReadahead; /// A pool from which materialized and scanned arrays will be allocated. MemoryPool* pool = arrow::default_memory_pool(); /// IOContext for any IO tasks /// /// Note: The IOContext executor will be ignored if use_threads is set to false io::IOContext io_context; /// If true the scanner will scan in parallel /// /// Note: If true, this will use threads from both the cpu_executor and the /// io_context.executor /// Note: This must be true in order for any readahead to happen bool use_threads = false; /// If true then an asycnhronous implementation of the scanner will be used. /// This implementation is newer and generally performs better. However, it /// makes extensive use of threading and is still considered experimental bool use_async = false; /// Fragment-specific scan options. std::shared_ptr fragment_scan_options; // Return a vector of fields that requires materialization. // // This is usually the union of the fields referenced in the projection and the // filter expression. Examples: // // - `SELECT a, b WHERE a < 2 && c > 1` => ["a", "b", "a", "c"] // - `SELECT a + b < 3 WHERE a > 1` => ["a", "b"] // // This is needed for expression where a field may not be directly // used in the final projection but is still required to evaluate the // expression. // // This is used by Fragment implementations to apply the column // sub-selection optimization. std::vector MaterializedFields() const; // Return a threaded or serial TaskGroup according to use_threads. std::shared_ptr<::arrow::internal::TaskGroup> TaskGroup() const; }; /// \brief Read record batches from a range of a single data fragment. A /// ScanTask is meant to be a unit of work to be dispatched. The implementation /// must be thread and concurrent safe. class ARROW_DS_EXPORT ScanTask { public: /// \brief Iterate through sequence of materialized record batches /// resulting from the Scan. Execution semantics are encapsulated in the /// particular ScanTask implementation virtual Result Execute() = 0; virtual Future SafeExecute(::arrow::internal::Executor* executor); virtual Future<> SafeVisit(::arrow::internal::Executor* executor, std::function)> visitor); virtual ~ScanTask() = default; const std::shared_ptr& options() const { return options_; } const std::shared_ptr& fragment() const { return fragment_; } protected: ScanTask(std::shared_ptr options, std::shared_ptr fragment) : options_(std::move(options)), fragment_(std::move(fragment)) {} std::shared_ptr options_; std::shared_ptr fragment_; }; /// \brief Combines a record batch with the fragment that the record batch originated /// from /// /// Knowing the source fragment can be useful for debugging & understanding loaded data struct TaggedRecordBatch { std::shared_ptr record_batch; std::shared_ptr fragment; }; using TaggedRecordBatchGenerator = std::function()>; using TaggedRecordBatchIterator = Iterator; /// \brief Combines a tagged batch with positional information /// /// This is returned when scanning batches in an unordered fashion. This information is /// needed if you ever want to reassemble the batches in order struct EnumeratedRecordBatch { Enumerated> record_batch; Enumerated> fragment; }; using EnumeratedRecordBatchGenerator = std::function()>; using EnumeratedRecordBatchIterator = Iterator; /// @} } // namespace dataset template <> struct IterationTraits { static dataset::TaggedRecordBatch End() { return dataset::TaggedRecordBatch{NULLPTR, NULLPTR}; } static bool IsEnd(const dataset::TaggedRecordBatch& val) { return val.record_batch == NULLPTR; } }; template <> struct IterationTraits { static dataset::EnumeratedRecordBatch End() { return dataset::EnumeratedRecordBatch{ IterationEnd>>(), IterationEnd>>()}; } static bool IsEnd(const dataset::EnumeratedRecordBatch& val) { return IsIterationEnd(val.fragment); } }; namespace dataset { /// \defgroup dataset-scanning Scanning API /// /// @{ /// \brief A scanner glues together several dataset classes to load in data. /// The dataset contains a collection of fragments and partitioning rules. /// /// The fragments identify independently loadable units of data (i.e. each fragment has /// a potentially unique schema and possibly even format. It should be possible to read /// fragments in parallel if desired). /// /// The fragment's format contains the logic necessary to actually create a task to load /// the fragment into memory. That task may or may not support parallel execution of /// its own. /// /// The scanner is then responsible for creating scan tasks from every fragment in the /// dataset and (potentially) sequencing the loaded record batches together. /// /// The scanner should not buffer the entire dataset in memory (unless asked) instead /// yielding record batches as soon as they are ready to scan. Various readahead /// properties control how much data is allowed to be scanned before pausing to let a /// slow consumer catchup. /// /// Today the scanner also handles projection & filtering although that may change in /// the future. class ARROW_DS_EXPORT Scanner { public: virtual ~Scanner() = default; /// \brief The Scan operator returns a stream of ScanTask. The caller is /// responsible to dispatch/schedule said tasks. Tasks should be safe to run /// in a concurrent fashion and outlive the iterator. /// /// Note: Not supported by the async scanner /// Planned for removal from the public API in ARROW-11782. ARROW_DEPRECATED("Deprecated in 4.0.0 for removal in 5.0.0. Use ScanBatches().") virtual Result Scan(); /// \brief Apply a visitor to each RecordBatch as it is scanned. If multiple threads /// are used (via use_threads), the visitor will be invoked from those threads and is /// responsible for any synchronization. virtual Status Scan(std::function visitor) = 0; /// \brief Convert a Scanner into a Table. /// /// Use this convenience utility with care. This will serially materialize the /// Scan result in memory before creating the Table. virtual Result> ToTable() = 0; /// \brief Scan the dataset into a stream of record batches. Each batch is tagged /// with the fragment it originated from. The batches will arrive in order. The /// order of fragments is determined by the dataset. /// /// Note: The scanner will perform some readahead but will avoid materializing too /// much in memory (this is goverended by the readahead options and use_threads option). /// If the readahead queue fills up then I/O will pause until the calling thread catches /// up. virtual Result ScanBatches() = 0; virtual Result ScanBatchesAsync() = 0; /// \brief Scan the dataset into a stream of record batches. Unlike ScanBatches this /// method may allow record batches to be returned out of order. This allows for more /// efficient scanning: some fragments may be accessed more quickly than others (e.g. /// may be cached in RAM or just happen to get scheduled earlier by the I/O) /// /// To make up for the out-of-order iteration each batch is further tagged with /// positional information. virtual Result ScanBatchesUnordered(); virtual Result ScanBatchesUnorderedAsync() = 0; /// \brief A convenience to synchronously load the given rows by index. /// /// Will only consume as many batches as needed from ScanBatches(). virtual Result> TakeRows(const Array& indices); /// \brief Get the first N rows. virtual Result> Head(int64_t num_rows); /// \brief Count rows matching a predicate. /// /// This method will push down the predicate and compute the result based on fragment /// metadata if possible. virtual Result CountRows(); /// \brief Convert the Scanner to a RecordBatchReader so it can be /// easily used with APIs that expect a reader. Result> ToRecordBatchReader(); /// \brief Get the options for this scan. const std::shared_ptr& options() const { return scan_options_; } /// \brief Get the dataset that this scanner will scan virtual const std::shared_ptr& dataset() const = 0; protected: explicit Scanner(std::shared_ptr scan_options) : scan_options_(std::move(scan_options)) {} Result AddPositioningToInOrderScan( TaggedRecordBatchIterator scan); const std::shared_ptr scan_options_; }; /// \brief ScannerBuilder is a factory class to construct a Scanner. It is used /// to pass information, notably a potential filter expression and a subset of /// columns to materialize. class ARROW_DS_EXPORT ScannerBuilder { public: explicit ScannerBuilder(std::shared_ptr dataset); ScannerBuilder(std::shared_ptr dataset, std::shared_ptr scan_options); ScannerBuilder(std::shared_ptr schema, std::shared_ptr fragment, std::shared_ptr scan_options); /// \brief Make a scanner from a record batch reader. /// /// The resulting scanner can be scanned only once. This is intended /// to support writing data from streaming sources or other sources /// that can be iterated only once. static std::shared_ptr FromRecordBatchReader( std::shared_ptr reader); /// \brief Set the subset of columns to materialize. /// /// Columns which are not referenced may not be read from fragments. /// /// \param[in] columns list of columns to project. Order and duplicates will /// be preserved. /// /// \return Failure if any column name does not exists in the dataset's /// Schema. Status Project(std::vector columns); /// \brief Set expressions which will be evaluated to produce the materialized /// columns. /// /// Columns which are not referenced may not be read from fragments. /// /// \param[in] exprs expressions to evaluate to produce columns. /// \param[in] names list of names for the resulting columns. /// /// \return Failure if any referenced column does not exists in the dataset's /// Schema. Status Project(std::vector exprs, std::vector names); /// \brief Set the filter expression to return only rows matching the filter. /// /// The predicate will be passed down to Sources and corresponding /// Fragments to exploit predicate pushdown if possible using /// partition information or Fragment internal metadata, e.g. Parquet statistics. /// Columns which are not referenced may not be read from fragments. /// /// \param[in] filter expression to filter rows with. /// /// \return Failure if any referenced columns does not exist in the dataset's /// Schema. Status Filter(const compute::Expression& filter); /// \brief Indicate if the Scanner should make use of the available /// ThreadPool found in ScanOptions; Status UseThreads(bool use_threads = true); /// \brief Limit how many fragments the scanner will read at once /// /// Note: This is only enforced in "async" mode Status FragmentReadahead(int fragment_readahead); /// \brief Indicate if the Scanner should run in experimental "async" mode /// /// This mode should have considerably better performance on high-latency or parallel /// filesystems but is still experimental Status UseAsync(bool use_async = true); /// \brief Set the maximum number of rows per RecordBatch. /// /// \param[in] batch_size the maximum number of rows. /// \returns An error if the number for batch is not greater than 0. /// /// This option provides a control limiting the memory owned by any RecordBatch. Status BatchSize(int64_t batch_size); /// \brief Set the pool from which materialized and scanned arrays will be allocated. Status Pool(MemoryPool* pool); /// \brief Set fragment-specific scan options. Status FragmentScanOptions(std::shared_ptr fragment_scan_options); /// \brief Return the constructed now-immutable Scanner object Result> Finish(); const std::shared_ptr& schema() const; const std::shared_ptr& projected_schema() const; private: std::shared_ptr dataset_; std::shared_ptr scan_options_ = std::make_shared(); }; /// \brief Construct a source ExecNode which yields batches from a dataset scan. /// /// Does not construct associated filter or project nodes. /// Yielded batches will be augmented with fragment/batch indices to enable stable /// ordering for simple ExecPlans. class ARROW_DS_EXPORT ScanNodeOptions : public compute::ExecNodeOptions { public: explicit ScanNodeOptions( std::shared_ptr dataset, std::shared_ptr scan_options, std::shared_ptr backpressure_toggle = NULLPTR, bool require_sequenced_output = false) : dataset(std::move(dataset)), scan_options(std::move(scan_options)), backpressure_toggle(std::move(backpressure_toggle)), require_sequenced_output(require_sequenced_output) {} std::shared_ptr dataset; std::shared_ptr scan_options; std::shared_ptr backpressure_toggle; bool require_sequenced_output; }; /// @} /// \brief A trivial ScanTask that yields the RecordBatch of an array. class ARROW_DS_EXPORT InMemoryScanTask : public ScanTask { public: InMemoryScanTask(std::vector> record_batches, std::shared_ptr options, std::shared_ptr fragment) : ScanTask(std::move(options), std::move(fragment)), record_batches_(std::move(record_batches)) {} Result Execute() override; protected: std::vector> record_batches_; }; namespace internal { ARROW_DS_EXPORT void InitializeScanner(arrow::compute::ExecFactoryRegistry* registry); } // namespace internal } // namespace dataset } // namespace arrow