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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.
import base64
from contextlib import contextmanager
from datetime import timedelta
import random
import pyarrow.fs as fs
import pyarrow as pa
import pytest
encryption_unavailable = False
try:
import pyarrow.parquet as pq
import pyarrow.dataset as ds
except ImportError:
pq = None
ds = None
try:
from pyarrow.tests.parquet.encryption import InMemoryKmsClient
import pyarrow.parquet.encryption as pe
except ImportError:
encryption_unavailable = True
# Marks all of the tests in this module
pytestmark = pytest.mark.dataset
FOOTER_KEY = b"0123456789112345"
FOOTER_KEY_NAME = "footer_key"
COL_KEY = b"1234567890123450"
COL_KEY_NAME = "col_key"
KEYS = {FOOTER_KEY_NAME: FOOTER_KEY, COL_KEY_NAME: COL_KEY}
EXTRA_COL_KEY = b"2345678901234501"
EXTRA_COL_KEY_NAME = "col2_key"
COLUMNS = ["year", "n_legs", "animal"]
COLUMN_KEYS = {COL_KEY_NAME: ["n_legs", "animal"]}
def create_sample_table():
return pa.table(
{
"year": [2020, 2022, 2021, 2022, 2019, 2021],
"n_legs": [2, 2, 4, 4, 5, 100],
"animal": [
"Flamingo",
"Parrot",
"Dog",
"Horse",
"Brittle stars",
"Centipede",
],
}
)
def create_encryption_config(footer_key=FOOTER_KEY_NAME, column_keys=COLUMN_KEYS):
return pe.EncryptionConfiguration(
footer_key=footer_key,
plaintext_footer=False,
column_keys=column_keys,
encryption_algorithm="AES_GCM_V1",
# requires timedelta or an assertion is raised
cache_lifetime=timedelta(minutes=5.0),
data_key_length_bits=256,
)
def create_decryption_config():
return pe.DecryptionConfiguration(cache_lifetime=300)
def create_kms_connection_config(keys=KEYS):
return pe.KmsConnectionConfig(
custom_kms_conf={
key_name: key.decode("UTF-8")
for key_name, key in keys.items()
}
)
def kms_factory(kms_connection_configuration):
return InMemoryKmsClient(kms_connection_configuration)
@contextmanager
def cond_raises(success, error_type, match):
if success:
yield
else:
with pytest.raises(error_type, match=match):
yield
def do_test_dataset_encryption_decryption(table, extra_column_path=None):
# use extra column key for column extra_column_path, if given
if extra_column_path:
keys = dict(**KEYS, **{EXTRA_COL_KEY_NAME: EXTRA_COL_KEY})
column_keys = dict(**COLUMN_KEYS, **{EXTRA_COL_KEY_NAME: [extra_column_path]})
extra_column_name = extra_column_path.split(".")[0]
else:
keys = KEYS
column_keys = COLUMN_KEYS
extra_column_name = None
# define the actual test
def assert_decrypts(
read_keys,
read_columns,
to_table_success,
dataset_success=True,
):
# use all keys for writing
write_keys = keys
encryption_config = create_encryption_config(FOOTER_KEY_NAME, column_keys)
decryption_config = create_decryption_config()
encrypt_kms_connection_config = create_kms_connection_config(write_keys)
decrypt_kms_connection_config = create_kms_connection_config(read_keys)
crypto_factory = pe.CryptoFactory(kms_factory)
parquet_encryption_cfg = ds.ParquetEncryptionConfig(
crypto_factory, encrypt_kms_connection_config, encryption_config
)
parquet_decryption_cfg = ds.ParquetDecryptionConfig(
crypto_factory, decrypt_kms_connection_config, decryption_config
)
# create write_options with dataset encryption config
pformat = pa.dataset.ParquetFileFormat()
write_options = pformat.make_write_options(
encryption_config=parquet_encryption_cfg
)
mockfs = fs._MockFileSystem()
mockfs.create_dir("/")
ds.write_dataset(
data=table,
base_dir="sample_dataset",
format=pformat,
file_options=write_options,
filesystem=mockfs,
)
# read without decryption config -> errors if dataset was properly encrypted
pformat = pa.dataset.ParquetFileFormat()
with pytest.raises(IOError, match=r"no decryption"):
ds.dataset("sample_dataset", format=pformat, filesystem=mockfs)
# set decryption config for parquet fragment scan options
pq_scan_opts = ds.ParquetFragmentScanOptions(
decryption_config=parquet_decryption_cfg
)
pformat = pa.dataset.ParquetFileFormat(
default_fragment_scan_options=pq_scan_opts
)
with cond_raises(dataset_success, ValueError, match="Unknown master key"):
dataset = ds.dataset("sample_dataset", format=pformat, filesystem=mockfs)
with cond_raises(to_table_success, ValueError, match="Unknown master key"):
assert table.select(read_columns).equals(dataset.to_table(read_columns))
# set decryption properties for parquet fragment scan options
decryption_properties = crypto_factory.file_decryption_properties(
decrypt_kms_connection_config, decryption_config)
pq_scan_opts = ds.ParquetFragmentScanOptions(
decryption_properties=decryption_properties
)
pformat = pa.dataset.ParquetFileFormat(
default_fragment_scan_options=pq_scan_opts
)
with cond_raises(dataset_success, ValueError, match="Unknown master key"):
dataset = ds.dataset("sample_dataset", format=pformat, filesystem=mockfs)
with cond_raises(to_table_success, ValueError, match="Unknown master key"):
assert table.select(read_columns).equals(dataset.to_table(read_columns))
# some notable column names and keys
all_column_names = table.column_names
encrypted_column_names = [column_name.split(".")[0]
for key_name, column_names in column_keys.items()
for column_name in column_names]
plaintext_column_names = [column_name
for column_name in all_column_names
if column_name not in encrypted_column_names and
(extra_column_path is None or
not extra_column_path.startswith(f"{column_name}."))]
assert len(encrypted_column_names) > 0
assert len(plaintext_column_names) > 0
footer_key_only = {FOOTER_KEY_NAME: FOOTER_KEY}
column_keys_only = {key_name: key
for key_name, key in keys.items()
if key_name != FOOTER_KEY_NAME}
# the test scenarios
# read with footer key only, can only read plaintext columns
assert_decrypts(footer_key_only, plaintext_column_names, True)
assert_decrypts(footer_key_only, encrypted_column_names, False)
assert_decrypts(footer_key_only, all_column_names, False)
# read with all but footer key, cannot read any columns
assert_decrypts(column_keys_only, plaintext_column_names, False, False)
assert_decrypts(column_keys_only, encrypted_column_names, False, False)
assert_decrypts(column_keys_only, all_column_names, False, False)
# with footer key and one column key, all plaintext and
# those encrypted columns that use that key, can be read
if len(column_keys) > 1:
for column_key_name, column_key_column_names in column_keys.items():
for encrypted_column_name in column_key_column_names:
# if one nested field of a column is encrypted,
# the entire column is considered encrypted
encrypted_column_name = encrypted_column_name.split(".")[0]
# decrypt with footer key and one column key
read_keys = {key_name: key
for key_name, key in keys.items()
if key_name in [FOOTER_KEY_NAME, column_key_name]}
# that one encrypted column can only be read
# if it is not a column path / nested field
plaintext_and_one_success = encrypted_column_name != extra_column_name
plaintext_and_one = plaintext_column_names + [encrypted_column_name]
assert_decrypts(read_keys, plaintext_column_names, True)
assert_decrypts(read_keys, plaintext_and_one, plaintext_and_one_success)
assert_decrypts(read_keys, encrypted_column_names, False)
assert_decrypts(read_keys, all_column_names, False)
# with all column keys, all columns can be read
assert_decrypts(keys, plaintext_column_names, True)
assert_decrypts(keys, encrypted_column_names, True)
assert_decrypts(keys, all_column_names, True)
@pytest.mark.skipif(
encryption_unavailable, reason="Parquet Encryption is not currently enabled"
)
def test_dataset_encryption_decryption():
do_test_dataset_encryption_decryption(create_sample_table())
@pytest.mark.skipif(
encryption_unavailable, reason="Parquet Encryption is not currently enabled"
)
@pytest.mark.parametrize("column_name", ["list", "list.list.element"])
def test_list_encryption_decryption(column_name):
list_data = pa.array(
[[1, 2, 3], [4, 5, 6], [7, 8, 9], [-1], [-2], [-3]],
type=pa.list_(pa.int32()),
)
table = create_sample_table().append_column("list", list_data)
do_test_dataset_encryption_decryption(table, column_name)
@pytest.mark.skipif(
encryption_unavailable,
reason="Parquet Encryption is not currently enabled"
)
@pytest.mark.parametrize(
"column_name", ["map", "map.key_value.key", "map.key_value.value"]
)
def test_map_encryption_decryption(column_name):
map_type = pa.map_(pa.string(), pa.int32())
map_data = pa.array(
[
[("k1", 1), ("k2", 2)], [("k1", 3), ("k3", 4)], [("k2", 5), ("k3", 6)],
[("k4", 7)], [], []
],
type=map_type
)
table = create_sample_table().append_column("map", map_data)
do_test_dataset_encryption_decryption(table, column_name)
@pytest.mark.skipif(
encryption_unavailable, reason="Parquet Encryption is not currently enabled"
)
@pytest.mark.parametrize("column_name", ["struct", "struct.f1", "struct.f2"])
def test_struct_encryption_decryption(column_name):
struct_fields = [("f1", pa.int32()), ("f2", pa.string())]
struct_type = pa.struct(struct_fields)
struct_data = pa.array(
[(1, "one"), (2, "two"), (3, "three"), (4, "four"), (5, "five"), (6, "six")],
type=struct_type
)
table = create_sample_table().append_column("struct", struct_data)
do_test_dataset_encryption_decryption(table, column_name)
@pytest.mark.skipif(
encryption_unavailable,
reason="Parquet Encryption is not currently enabled"
)
@pytest.mark.parametrize(
"column_name",
[
"col",
"col.list.element.key_value.key",
"col.list.element.key_value.value.f1",
"col.list.element.key_value.value.f2"
]
)
def test_deep_nested_encryption_decryption(column_name):
struct_fields = [("f1", pa.int32()), ("f2", pa.string())]
struct_type = pa.struct(struct_fields)
struct1 = (1, "one")
struct2 = (2, "two")
struct3 = (3, "three")
struct4 = (4, "four")
struct5 = (5, "five")
struct6 = (6, "six")
map_type = pa.map_(pa.int32(), struct_type)
map1 = {1: struct1, 2: struct2}
map2 = {3: struct3}
map3 = {4: struct4}
map4 = {5: struct5, 6: struct6}
list_type = pa.list_(map_type)
list1 = [map1, map2]
list2 = [map3]
list3 = [map4]
list_data = [pa.array([list1, list2, None, list3, None, None], type=list_type)]
table = create_sample_table().append_column("col", list_data)
do_test_dataset_encryption_decryption(table, column_name)
@pytest.mark.skipif(
not encryption_unavailable, reason="Parquet Encryption is currently enabled"
)
def test_write_dataset_parquet_without_encryption():
"""Test write_dataset with ParquetFileFormat and test if an exception is thrown
if you try to set encryption_config using make_write_options"""
# Set the encryption configuration using ParquetFileFormat
# and make_write_options
pformat = pa.dataset.ParquetFileFormat()
with pytest.raises(NotImplementedError):
_ = pformat.make_write_options(encryption_config="some value")
@pytest.mark.skipif(
encryption_unavailable, reason="Parquet Encryption is not currently enabled"
)
def test_large_row_encryption_decryption():
"""Test encryption and decryption of a large number of rows."""
class NoOpKmsClient(pe.KmsClient):
def wrap_key(self, key_bytes: bytes, _: str) -> bytes:
b = base64.b64encode(key_bytes)
return b
def unwrap_key(self, wrapped_key: bytes, _: str) -> bytes:
b = base64.b64decode(wrapped_key)
return b
row_count = 2**15 + 1
table = pa.Table.from_arrays(
[pa.array(
[random.random() for _ in range(row_count)],
type=pa.float32()
)], names=["foo"]
)
kms_config = pe.KmsConnectionConfig()
crypto_factory = pe.CryptoFactory(lambda _: NoOpKmsClient())
encryption_config = pe.EncryptionConfiguration(
footer_key="UNIMPORTANT_KEY",
column_keys={"UNIMPORTANT_KEY": ["foo"]},
double_wrapping=True,
plaintext_footer=False,
data_key_length_bits=128,
)
pqe_config = ds.ParquetEncryptionConfig(
crypto_factory, kms_config, encryption_config
)
pqd_config = ds.ParquetDecryptionConfig(
crypto_factory, kms_config, pe.DecryptionConfiguration()
)
scan_options = ds.ParquetFragmentScanOptions(decryption_config=pqd_config)
file_format = ds.ParquetFileFormat(default_fragment_scan_options=scan_options)
write_options = file_format.make_write_options(encryption_config=pqe_config)
file_decryption_properties = crypto_factory.file_decryption_properties(kms_config)
mockfs = fs._MockFileSystem()
mockfs.create_dir("/")
path = "large-row-test-dataset"
ds.write_dataset(table, path, format=file_format,
file_options=write_options, filesystem=mockfs)
file_path = path + "/part-0.parquet"
new_table = pq.ParquetFile(
file_path, decryption_properties=file_decryption_properties,
filesystem=mockfs
).read()
assert table == new_table
dataset = ds.dataset(path, format=file_format, filesystem=mockfs)
new_table = dataset.to_table()
assert table == new_table
@pytest.mark.skipif(
encryption_unavailable, reason="Parquet Encryption is not currently enabled"
)
def test_dataset_encryption_with_selected_column_statistics():
table = create_sample_table()
encryption_config = create_encryption_config()
decryption_config = create_decryption_config()
kms_connection_config = create_kms_connection_config()
crypto_factory = pe.CryptoFactory(kms_factory)
parquet_encryption_cfg = ds.ParquetEncryptionConfig(
crypto_factory, kms_connection_config, encryption_config
)
parquet_decryption_cfg = ds.ParquetDecryptionConfig(
crypto_factory, kms_connection_config, decryption_config
)
# create write_options with dataset encryption config
# and specify that statistics should be enabled for a subset of columns.
pformat = pa.dataset.ParquetFileFormat()
write_options = pformat.make_write_options(
encryption_config=parquet_encryption_cfg,
write_statistics=["year", "n_legs"]
)
mockfs = fs._MockFileSystem()
mockfs.create_dir("/")
ds.write_dataset(
data=table,
base_dir="sample_dataset",
format=pformat,
file_options=write_options,
filesystem=mockfs,
)
# Open Parquet files directly and check that statistics are present
# for the expected columns.
pq_scan_opts = ds.ParquetFragmentScanOptions(
decryption_config=parquet_decryption_cfg
)
pformat = pa.dataset.ParquetFileFormat(default_fragment_scan_options=pq_scan_opts)
dataset = ds.dataset("sample_dataset", format=pformat, filesystem=mockfs)
for fragment in dataset.get_fragments():
decryption_properties = crypto_factory.file_decryption_properties(
kms_connection_config, decryption_config, fragment.path, mockfs)
with pq.ParquetFile(
fragment.path,
decryption_properties=decryption_properties,
filesystem=mockfs,
) as parquet_file:
for rg_idx in range(parquet_file.metadata.num_row_groups):
row_group = parquet_file.metadata.row_group(rg_idx)
assert row_group.column(0).statistics is not None
assert row_group.column(0).statistics.min == 2019
assert row_group.column(0).statistics.max == 2022
assert row_group.column(1).statistics is not None
assert row_group.column(1).statistics.min == 2
assert row_group.column(1).statistics.max == 100
assert row_group.column(2).statistics is None
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