Files
arrow/python/pyarrow/tests/test_dataset_encryption.py
Dricmoy Bhattacharjee 1776578067 GH-51351: [C++][Parquet] Use default KMS connection values (#53996)
### Rationale for this change

`FileKeyWrapper` calls `SetDefaultIfEmpty()` on its stored configuration, but passes the original, unmodified configuration to `GetKmsClient`. This allows the KMS client factory to receive empty instance ID and URL values even though Arrow has already filled in defaults on its internal copy.

### What changes are included in this PR?

- Pass the defaulted `kms_connection_config_` member to `GetKmsClient`.
- Update C++ and Python key-rotation tests to expect Arrow's existing default values for empty fields.
- Separate the writer and reader crypto factories in the dataset encryption tests.

The dataset tests give the writer all keys and the reader only some. With a shared factory, the reader can reuse the writer's cached client, which already has all the keys. Separate factories ensure the reader uses its own keys, so the missing-key checks work correctly. The write-path fix exposes this because writing and reading now use the same default instance ID, where empty and `"DEFAULT"` IDs previously selected separate cache entries.

### Are these changes tested?

- Local C++ encryption key-management suite: 24 tests passed.
- Both local Python encryption test files: 62 passed, 1 skipped. The skipped case requires a build without encryption support.
- C++ and Python formatting and lint, and `git diff --check`, passed.
- Fork CI for `537e296384`: [Python](https://github.com/Dricmoy/arrow/actions/runs/38923806919), [Dev](https://github.com/Dricmoy/arrow/actions/runs/38923806888), and [Docs](https://github.com/Dricmoy/arrow/actions/runs/38923806885) passed. The [C++ workflow](https://github.com/Dricmoy/arrow/actions/runs/38852310915) passed for the preceding commit; the follow-up commit changes only Python tests.

### Are there any user-facing changes?

KMS client factories receive Arrow's `"DEFAULT"` markers instead of empty strings for omitted instance ID and URL values. Explicit non-empty values are preserved. These markers are interpreted by the KMS implementation; they are not automatically resolved server addresses.

I reviewed the compatibility tradeoff: custom factories that special-case empty strings may need updating. Defaulting the instance ID can also change client reuse because the cache is indexed by access token and instance ID. Requests with the same token and resolved ID can now share a client where empty and `"DEFAULT"` IDs previously selected separate entries. This makes client creation consistent with Arrow's existing defaulting logic and stored key metadata, but changes behavior for integrations that rely on empty strings. There are no API signature changes.

Closes #51351. Follow-up to #53949.

### Was AI used for this PR?

AI assisted with the implementation, tests, validation, and this description. I reviewed the configuration flow, the default-value test expectations, the reader/writer cache separation, and the compatibility tradeoff described above. The PR overall is fairly small consistent expectation change, had some tests changed to fit the updated expectations.

**PR code and description written by:**

- [x] Human
- [x] AI

**Reviewed before submission by:**

- [x] Human
- [x] AI
- [ ] Not reviewed

* GitHub Issue: #51351

Authored-by: Dricmoy <dricbhattacharjee@gmail.com>
Signed-off-by: Adam Reeve <adreeve@gmail.com>
2026-10-21 11:03:46 +13:00

490 lines
17 KiB
Python

# 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]})
else:
keys = KEYS
column_keys = COLUMN_KEYS
# 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)
encrypt_crypto_factory = pe.CryptoFactory(kms_factory)
# Keep the writer's cached keys out of the reader's configuration.
decrypt_crypto_factory = pe.CryptoFactory(kms_factory)
parquet_encryption_cfg = ds.ParquetEncryptionConfig(
encrypt_crypto_factory, encrypt_kms_connection_config, encryption_config
)
parquet_decryption_cfg = ds.ParquetDecryptionConfig(
decrypt_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 = decrypt_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]}
plaintext_and_one = plaintext_column_names + [encrypted_column_name]
assert_decrypts(read_keys, plaintext_column_names, True)
assert_decrypts(read_keys, plaintext_and_one, True)
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