[
https://issues.apache.org/jira/browse/ARROW-2307?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16399687#comment-16399687
]
ASF GitHub Bot commented on ARROW-2307:
---------------------------------------
wesm closed pull request #1747: ARROW-2307: [Python] Allow reading record batch
streams with zero record batches
URL: https://github.com/apache/arrow/pull/1747
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):
diff --git a/ci/msvc-build.bat b/ci/msvc-build.bat
index beefee6c0..a29ef0bad 100644
--- a/ci/msvc-build.bat
+++ b/ci/msvc-build.bat
@@ -69,7 +69,8 @@ if "%JOB%" == "Build_Debug" (
)
conda create -n arrow -q -y python=%PYTHON% ^
- six pytest setuptools numpy pandas cython ^
+ six pytest setuptools numpy pandas ^
+ cython=0.27.3 ^
thrift-cpp=0.11.0
call activate arrow
diff --git a/ci/travis_script_python.sh b/ci/travis_script_python.sh
index a776c4263..247d10278 100755
--- a/ci/travis_script_python.sh
+++ b/ci/travis_script_python.sh
@@ -41,7 +41,7 @@ conda install -y -q pip \
cloudpickle \
numpy=1.13.1 \
pandas \
- cython
+ cython=0.27.3
# ARROW-2093: PyTorch increases the size of our conda dependency stack
# significantly, and so we have disabled these tests in Travis CI for now
diff --git a/cpp/src/arrow/table-test.cc b/cpp/src/arrow/table-test.cc
index 24c8d5e15..b1cf6e59a 100644
--- a/cpp/src/arrow/table-test.cc
+++ b/cpp/src/arrow/table-test.cc
@@ -374,6 +374,17 @@ TEST_F(TestTable, FromRecordBatches) {
ASSERT_RAISES(Invalid, Table::FromRecordBatches({batch1, batch2}, &result));
}
+TEST_F(TestTable, FromRecordBatchesZeroLength) {
+ // ARROW-2307
+ MakeExample1(10);
+
+ std::shared_ptr<Table> result;
+ ASSERT_OK(Table::FromRecordBatches(schema_, {}, &result));
+
+ ASSERT_EQ(0, result->num_rows());
+ ASSERT_TRUE(result->schema()->Equals(*schema_));
+}
+
TEST_F(TestTable, ConcatenateTables) {
const int64_t length = 10;
diff --git a/cpp/src/arrow/table.cc b/cpp/src/arrow/table.cc
index ed5858624..f6ac6dd3b 100644
--- a/cpp/src/arrow/table.cc
+++ b/cpp/src/arrow/table.cc
@@ -297,14 +297,9 @@ std::shared_ptr<Table> Table::Make(const
std::shared_ptr<Schema>& schema,
return std::make_shared<SimpleTable>(schema, arrays, num_rows);
}
-Status Table::FromRecordBatches(const
std::vector<std::shared_ptr<RecordBatch>>& batches,
+Status Table::FromRecordBatches(const std::shared_ptr<Schema>& schema,
+ const
std::vector<std::shared_ptr<RecordBatch>>& batches,
std::shared_ptr<Table>* table) {
- if (batches.size() == 0) {
- return Status::Invalid("Must pass at least one record batch");
- }
-
- std::shared_ptr<Schema> schema = batches[0]->schema();
-
const int nbatches = static_cast<int>(batches.size());
const int ncolumns = static_cast<int>(schema->num_fields());
@@ -332,6 +327,15 @@ Status Table::FromRecordBatches(const
std::vector<std::shared_ptr<RecordBatch>>&
return Status::OK();
}
+Status Table::FromRecordBatches(const
std::vector<std::shared_ptr<RecordBatch>>& batches,
+ std::shared_ptr<Table>* table) {
+ if (batches.size() == 0) {
+ return Status::Invalid("Must pass at least one record batch");
+ }
+
+ return FromRecordBatches(batches[0]->schema(), batches, table);
+}
+
Status ConcatenateTables(const std::vector<std::shared_ptr<Table>>& tables,
std::shared_ptr<Table>* table) {
if (tables.size() == 0) {
diff --git a/cpp/src/arrow/table.h b/cpp/src/arrow/table.h
index 7274fca4d..20d027d6a 100644
--- a/cpp/src/arrow/table.h
+++ b/cpp/src/arrow/table.h
@@ -169,9 +169,25 @@ class ARROW_EXPORT Table {
const
std::vector<std::shared_ptr<Array>>& arrays,
int64_t num_rows = -1);
- // Construct table from RecordBatch, but only if all of the batch schemas are
- // equal. Returns Status::Invalid if there is some problem
+ /// \brief Construct table from RecordBatches, using schema supplied by the
first
+ /// RecordBatch.
+ ///
+ /// \param[in] batches a std::vector of record batches
+ /// \param[out] table the returned table
+ /// \return Status Returns Status::Invalid if there is some problem
+ static Status FromRecordBatches(
+ const std::vector<std::shared_ptr<RecordBatch>>& batches,
+ std::shared_ptr<Table>* table);
+
+ /// Construct table from RecordBatches, using supplied schema. There may be
+ /// zero record batches
+ ///
+ /// \param[in] schema the arrow::Schema for each batch
+ /// \param[in] batches a std::vector of record batches
+ /// \param[out] table the returned table
+ /// \return Status
static Status FromRecordBatches(
+ const std::shared_ptr<Schema>& schema,
const std::vector<std::shared_ptr<RecordBatch>>& batches,
std::shared_ptr<Table>* table);
diff --git a/python/pyarrow/includes/libarrow.pxd
b/python/pyarrow/includes/libarrow.pxd
index 3d0c02b89..01a641896 100644
--- a/python/pyarrow/includes/libarrow.pxd
+++ b/python/pyarrow/includes/libarrow.pxd
@@ -456,6 +456,7 @@ cdef extern from "arrow/api.h" namespace "arrow" nogil:
@staticmethod
CStatus FromRecordBatches(
+ const shared_ptr[CSchema]& schema,
const vector[shared_ptr[CRecordBatch]]& batches,
shared_ptr[CTable]* table)
diff --git a/python/pyarrow/ipc.pxi b/python/pyarrow/ipc.pxi
index a30a228ae..f2ba6b692 100644
--- a/python/pyarrow/ipc.pxi
+++ b/python/pyarrow/ipc.pxi
@@ -304,7 +304,8 @@ cdef class _RecordBatchReader:
break
batches.push_back(batch)
- check_status(CTable.FromRecordBatches(batches, &table))
+ check_status(CTable.FromRecordBatches(self.schema.sp_schema,
+ batches, &table))
return pyarrow_wrap_table(table)
@@ -386,7 +387,8 @@ cdef class _RecordBatchFileReader:
with nogil:
for i in range(nbatches):
check_status(self.reader.get().ReadRecordBatch(i, &batches[i]))
- check_status(CTable.FromRecordBatches(batches, &table))
+ check_status(CTable.FromRecordBatches(self.schema.sp_schema,
+ batches, &table))
return pyarrow_wrap_table(table)
diff --git a/python/pyarrow/table.pxi b/python/pyarrow/table.pxi
index 94041e465..6cfa9873b 100644
--- a/python/pyarrow/table.pxi
+++ b/python/pyarrow/table.pxi
@@ -975,7 +975,7 @@ cdef class Table:
columns.reserve(K)
for i in range(K):
- if isinstance(arrays[i], Array):
+ if isinstance(arrays[i], (Array, list)):
columns.push_back(
make_shared[CColumn](
c_schema.get().field(i),
@@ -1003,26 +1003,41 @@ cdef class Table:
return pyarrow_wrap_table(CTable.Make(c_schema, columns))
@staticmethod
- def from_batches(batches):
+ def from_batches(batches, Schema schema=None):
"""
Construct a Table from a list of Arrow RecordBatches
Parameters
----------
-
batches: list of RecordBatch
- RecordBatch list to be converted, schemas must be equal
+ RecordBatch list to be converted, all schemas must be equal
+ schema : Schema, default None
+ If not passed, will be inferred from the first RecordBatch
+
+ Returns
+ -------
+ table : Table
"""
cdef:
vector[shared_ptr[CRecordBatch]] c_batches
shared_ptr[CTable] c_table
+ shared_ptr[CSchema] c_schema
RecordBatch batch
for batch in batches:
c_batches.push_back(batch.sp_batch)
+ if schema is None:
+ if len(batches) == 0:
+ raise ValueError('Must pass schema, or at least '
+ 'one RecordBatch')
+ c_schema = c_batches[0].get().schema()
+ else:
+ c_schema = schema.sp_schema
+
with nogil:
- check_status(CTable.FromRecordBatches(c_batches, &c_table))
+ check_status(CTable.FromRecordBatches(c_schema, c_batches,
+ &c_table))
return pyarrow_wrap_table(c_table)
diff --git a/python/pyarrow/tests/test_ipc.py b/python/pyarrow/tests/test_ipc.py
index 9cd5f8076..c31c32251 100644
--- a/python/pyarrow/tests/test_ipc.py
+++ b/python/pyarrow/tests/test_ipc.py
@@ -379,6 +379,24 @@ def test_ipc_zero_copy_numpy():
assert_frame_equal(df, rdf)
+def test_ipc_stream_no_batches():
+ # ARROW-2307
+ table = pa.Table.from_arrays([pa.array([1, 2, 3, 4]),
+ pa.array(['foo', 'bar', 'baz', 'qux'])],
+ names=['a', 'b'])
+
+ sink = pa.BufferOutputStream()
+ writer = pa.RecordBatchStreamWriter(sink, table.schema)
+ writer.close()
+
+ source = sink.get_result()
+ reader = pa.open_stream(source)
+ result = reader.read_all()
+
+ assert result.schema.equals(table.schema)
+ assert len(result) == 0
+
+
def test_get_record_batch_size():
N = 10
itemsize = 8
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> [Python] Unable to read arrow stream containing 0 record batches
> ----------------------------------------------------------------
>
> Key: ARROW-2307
> URL: https://issues.apache.org/jira/browse/ARROW-2307
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.8.0
> Reporter: Benjamin Duffield
> Assignee: Wes McKinney
> Priority: Major
> Labels: pull-request-available
> Fix For: 0.9.0
>
>
> Using java arrow I'm creating an arrow stream, using the stream writer.
>
> Sometimes I don't have anything to serialize, and so I don't write any record
> batches. My arrow stream thus consists of just a schema message.
> {code:java}
> <SCHEMA>
> <EOS [optional]: int32>
> {code}
> I am able to deserialize this arrow stream correctly using the java stream
> reader, but when reading it with python I instead hit an error
> {code}
> import pyarrow as pa
> # ...
> reader = pa.open_stream(stream)
> df = reader.read_all().to_pandas()
> {code}
> produces
> {code}
> File "ipc.pxi", line 307, in pyarrow.lib._RecordBatchReader.read_all
> File "error.pxi", line 77, in pyarrow.lib.check_status
> ArrowInvalid: Must pass at least one record batch
> {code}
> i.e. we're hitting the check in
> https://github.com/apache/arrow/blob/apache-arrow-0.8.0/cpp/src/arrow/table.cc#L284
> The workaround we're currently using is to always ensure we serialize at
> least one record batch, even if it's empty. However, I think it would be nice
> to either support a stream without record batches or explicitly disallow this
> and then match behaviour in java.
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