def test_parquet_dask(gp_multipoint, gp_multiline, tmp_path):
# Build dataframe
n = min(len(gp_multipoint), len(gp_multiline))
df = GeoDataFrame({
'points': GeoSeries(gp_multipoint[:n]),
'lines': GeoSeries(gp_multiline[:n]),
'a': list(range(n))
})
ddf = dd.from_pandas(df, npartitions=3)
path = tmp_path / 'ddf.parq'
ddf.to_parquet(path)
ddf_read = read_parquet_dask(path)
# Check type
assert isinstance(ddf_read, DaskGeoDataFrame)
# Check that partition bounds were loaded
assert set(ddf_read._partition_bounds) == {'points', 'lines'}
pd.testing.assert_frame_equal(
ddf['points'].partition_bounds,
ddf_read._partition_bounds['points'],
)
pd.testing.assert_frame_equal(
ddf['lines'].partition_bounds,
ddf_read._partition_bounds['lines'],
)
def test_pack_partitions_to_parquet_glob(gp_multipoint1, gp_multiline1,
gp_multipoint2, gp_multiline2,
tmp_path):
# Build dataframe1
n = min(len(gp_multipoint1), len(gp_multiline1))
df1 = GeoDataFrame({
'points': GeoSeries(gp_multipoint1[:n]),
'lines': GeoSeries(gp_multiline1[:n]),
'a': list(range(n))
}).set_geometry('lines')
ddf1 = dd.from_pandas(df1, npartitions=3)
path1 = tmp_path / 'ddf1.parq'
ddf_packed1 = ddf1.pack_partitions_to_parquet(str(path1), npartitions=3)
# Build dataframe2
n = min(len(gp_multipoint2), len(gp_multiline2))
df2 = GeoDataFrame({
'points': GeoSeries(gp_multipoint2[:n]),
'lines': GeoSeries(gp_multiline2[:n]),
'a': list(range(n))
}).set_geometry('lines')
ddf2 = dd.from_pandas(df2, npartitions=3)
path2 = tmp_path / 'ddf2.parq'
ddf_packed2 = ddf2.pack_partitions_to_parquet(str(path2), npartitions=4)
# Load both packed datasets with glob
ddf_globbed = read_parquet_dask(tmp_path / "ddf*.parq", geometry="lines")
# Check the number of partitions (< 7 can happen in the case of empty partitions)
assert ddf_globbed.npartitions <= 7
# Check contents
expected_df = pd.concat([ddf_packed1.compute(), ddf_packed2.compute()])
df_globbed = ddf_globbed.compute()
pd.testing.assert_frame_equal(df_globbed, expected_df)
# Check partition bounds
expected_bounds = {
'points':
pd.concat([
ddf_packed1._partition_bounds['points'],
ddf_packed2._partition_bounds['points'],
]).reset_index(drop=True),
'lines':
pd.concat([
ddf_packed1._partition_bounds['lines'],
ddf_packed2._partition_bounds['lines'],
]).reset_index(drop=True),
}
expected_bounds['points'].index.name = 'partition'
expected_bounds['lines'].index.name = 'partition'
pd.testing.assert_frame_equal(expected_bounds['points'],
ddf_globbed._partition_bounds['points'])
pd.testing.assert_frame_equal(expected_bounds['lines'],
ddf_globbed._partition_bounds['lines'])
assert ddf_globbed.geometry.name == 'lines'
def test_pack_partitions_to_parquet(gp_multipoint, gp_multiline,
use_temp_format, tmp_path_factory):
with tmp_path_factory.mktemp("spatialpandas", numbered=True) as tmp_path:
# Build dataframe
n = min(len(gp_multipoint), len(gp_multiline))
df = GeoDataFrame({
'points': GeoSeries(gp_multipoint[:n]),
'lines': GeoSeries(gp_multiline[:n]),
'a': list(range(n))
}).set_geometry('lines')
ddf = dd.from_pandas(df, npartitions=3)
path = tmp_path / 'ddf.parq'
if use_temp_format:
(tmp_path / 'scratch').mkdir(parents=True, exist_ok=True)
tempdir_format = str(tmp_path / 'scratch' /
'part-{uuid}-{partition:03d}')
else:
tempdir_format = None
_retry_args = dict(wait_exponential_multiplier=10,
wait_exponential_max=20000,
stop_max_attempt_number=4)
ddf_packed = ddf.pack_partitions_to_parquet(
str(path),
npartitions=12,
tempdir_format=tempdir_format,
_retry_args=_retry_args,
)
# Check the number of partitions (< 4 can happen in the case of empty partitions)
assert ddf_packed.npartitions <= 12
# Check that rows are now sorted in order of hilbert distance
total_bounds = df.lines.total_bounds
hilbert_distances = ddf_packed.lines.map_partitions(
lambda s: s.hilbert_distance(total_bounds=total_bounds)).compute(
).values
# Compute expected total_bounds
expected_distances = np.sort(
df.lines.hilbert_distance(total_bounds=total_bounds).values)
np.testing.assert_equal(expected_distances, hilbert_distances)
assert ddf_packed.geometry.name == 'points'
# Read columns
columns = ['a', 'lines']
ddf_read_cols = read_parquet_dask(path, columns=columns)
pd.testing.assert_frame_equal(ddf_read_cols.compute(),
ddf_packed[columns].compute())
def load_trajectory_table(root_path, year, month, espg=2845, head=None):
"""helper to load the trajectory table"""
input_path = f"{root_path}/{year}/{month}"
# read parquet file(s) from disk
ddf = read_parquet_dask(input_path)
# bring it all into memory, convert to a geopandas GeoDataFrame, and set CRS
if head:
gdf = ddf.head(head).to_geopandas().set_crs(f"EPSG:{espg}")
else:
gdf = ddf.compute().to_geopandas().set_crs(f"EPSG:{espg}")
return gdf
def test_pack_partitions_to_parquet(gp_multipoint, gp_multiline,
use_temp_format, tmp_path):
# Build dataframe
n = min(len(gp_multipoint), len(gp_multiline))
df = GeoDataFrame({
'points': GeoSeries(gp_multipoint[:n]),
'lines': GeoSeries(gp_multiline[:n]),
'a': list(range(n))
}).set_geometry('lines')
ddf = dd.from_pandas(df, npartitions=3)
path = tmp_path / 'ddf.parq'
if use_temp_format:
tempdir_format = str(tmp_path / 'scratch' /
'part-{uuid}-{partition:03d}')
else:
tempdir_format = None
ddf_packed = ddf.pack_partitions_to_parquet(path,
npartitions=12,
tempdir_format=tempdir_format)
# Check the number of partitions (< 4 can happen in the case of empty partitions)
assert ddf_packed.npartitions <= 12
# Check that rows are now sorted in order of hilbert distance
total_bounds = df.lines.total_bounds
hilbert_distances = ddf_packed.lines.map_partitions(
lambda s: s.hilbert_distance(total_bounds=total_bounds)).compute(
).values
# Compute expected total_bounds
expected_distances = np.sort(
df.lines.hilbert_distance(total_bounds=total_bounds).values)
np.testing.assert_equal(expected_distances, hilbert_distances)
assert ddf_packed.geometry.name == 'points'
# Read columns
columns = ['a', 'lines']
ddf_read_cols = read_parquet_dask(path,
columns=columns + ['hilbert_distance'])
pd.testing.assert_frame_equal(ddf_read_cols.compute(),
ddf_packed[columns].compute())
def test_parquet_dask(gp_multipoint, gp_multiline, tmp_path_factory):
with tmp_path_factory.mktemp("spatialpandas", numbered=True) as tmp_path:
# Build dataframe
n = min(len(gp_multipoint), len(gp_multiline))
df = GeoDataFrame({
'points': GeoSeries(gp_multipoint[:n]),
'lines': GeoSeries(gp_multiline[:n]),
'a': list(range(n))
})
ddf = dd.from_pandas(df, npartitions=3)
path = tmp_path / 'ddf.parq'
ddf.to_parquet(str(path))
ddf_read = read_parquet_dask(str(path))
# Check type
assert isinstance(ddf_read, DaskGeoDataFrame)
# Check that partition bounds were loaded
nonempty = np.nonzero(
np.asarray(ddf.map_partitions(len).compute() > 0))[0]
assert set(ddf_read._partition_bounds) == {'points', 'lines'}
expected_partition_bounds = (
ddf['points'].partition_bounds.iloc[nonempty].reset_index(
drop=True))
expected_partition_bounds.index.name = 'partition'
pd.testing.assert_frame_equal(
expected_partition_bounds,
ddf_read._partition_bounds['points'],
)
expected_partition_bounds = (
ddf['lines'].partition_bounds.iloc[nonempty].reset_index(
drop=True))
expected_partition_bounds.index.name = 'partition'
pd.testing.assert_frame_equal(
expected_partition_bounds,
ddf_read._partition_bounds['lines'],
)
assert ddf_read.geometry.name == 'points'
def test_pack_partitions_to_parquet_list_bounds(
gp_multipoint1,
gp_multiline1,
gp_multipoint2,
gp_multiline2,
bounds,
tmp_path,
):
# Build dataframe1
n = min(len(gp_multipoint1), len(gp_multiline1))
df1 = GeoDataFrame({
'points': GeoSeries(gp_multipoint1[:n]),
'lines': GeoSeries(gp_multiline1[:n]),
'a': list(range(n))
}).set_geometry('lines')
ddf1 = dd.from_pandas(df1, npartitions=3)
path1 = tmp_path / 'ddf1.parq'
ddf_packed1 = ddf1.pack_partitions_to_parquet(str(path1), npartitions=3)
# Build dataframe2
n = min(len(gp_multipoint2), len(gp_multiline2))
df2 = GeoDataFrame({
'points': GeoSeries(gp_multipoint2[:n]),
'lines': GeoSeries(gp_multiline2[:n]),
'a': list(range(n))
}).set_geometry('lines')
ddf2 = dd.from_pandas(df2, npartitions=3)
path2 = tmp_path / 'ddf2.parq'
ddf_packed2 = ddf2.pack_partitions_to_parquet(str(path2), npartitions=4)
# Load both packed datasets with glob
ddf_read = read_parquet_dask(
[str(tmp_path / "ddf1.parq"),
str(tmp_path / "ddf2.parq")],
geometry="points",
bounds=bounds)
# Check the number of partitions (< 7 can happen in the case of empty partitions)
assert ddf_read.npartitions <= 7
# Check contents
xslice = slice(bounds[0], bounds[2])
yslice = slice(bounds[1], bounds[3])
expected_df = pd.concat([
ddf_packed1.cx_partitions[xslice, yslice].compute(),
ddf_packed2.cx_partitions[xslice, yslice].compute()
])
df_read = ddf_read.compute()
pd.testing.assert_frame_equal(df_read, expected_df)
# Compute expected partition bounds
points_bounds = pd.concat([
ddf_packed1._partition_bounds['points'],
ddf_packed2._partition_bounds['points'],
]).reset_index(drop=True)
x0, y0, x1, y1 = bounds
x0, x1 = (x0, x1) if x0 <= x1 else (x1, x0)
y0, y1 = (y0, y1) if y0 <= y1 else (y1, y0)
partition_inds = ~((points_bounds.x1 < x0) | (points_bounds.y1 < y0) |
(points_bounds.x0 > x1) | (points_bounds.y0 > y1))
points_bounds = points_bounds[partition_inds].reset_index(drop=True)
lines_bounds = pd.concat([
ddf_packed1._partition_bounds['lines'],
ddf_packed2._partition_bounds['lines'],
]).reset_index(drop=True)[partition_inds].reset_index(drop=True)
points_bounds.index.name = 'partition'
lines_bounds.index.name = 'partition'
# Check partition bounds
pd.testing.assert_frame_equal(points_bounds,
ddf_read._partition_bounds['points'])
pd.testing.assert_frame_equal(lines_bounds,
ddf_read._partition_bounds['lines'])
# Check active geometry column
assert ddf_read.geometry.name == 'points'