mirror of
https://github.com/open-metadata/OpenMetadata.git
synced 2025-10-30 18:17:53 +00:00
9a4a9df836
* linting: fix python linting * fix: get column types from parquet schema for parquet files * style: python linting * fix: remove displayType check in test as variation depending on OS
447 lines
16 KiB
Python
447 lines
16 KiB
Python
# Copyright 2021 Collate
|
|
# Licensed 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.
|
|
"""
|
|
Test datalake utils
|
|
"""
|
|
|
|
import os
|
|
from unittest import TestCase
|
|
|
|
import pandas as pd
|
|
|
|
from metadata.generated.schema.entity.data.table import Column, DataType
|
|
from metadata.readers.dataframe.reader_factory import SupportedTypes
|
|
from metadata.utils.datalake.datalake_utils import (
|
|
DataFrameColumnParser,
|
|
GenericDataFrameColumnParser,
|
|
ParquetDataFrameColumnParser,
|
|
)
|
|
|
|
STRUCTURE = {
|
|
"a": "w",
|
|
"b": 4,
|
|
"c": {
|
|
"d": 2,
|
|
"e": 4,
|
|
"f": {
|
|
"g": 9,
|
|
"h": {"i": 6},
|
|
"n": {
|
|
"o": 10,
|
|
"p": 11,
|
|
},
|
|
},
|
|
"j": 7,
|
|
"k": 8,
|
|
},
|
|
}
|
|
|
|
|
|
class TestDatalakeUtils(TestCase):
|
|
"""class for datalake utils test"""
|
|
|
|
def test_unique_json_structure(self):
|
|
"""test unique json structure fn"""
|
|
sample_data = [
|
|
{"a": "x", "b": 1, "c": {"d": 2}},
|
|
{"a": "y", "b": 2, "c": {"e": 4, "f": {"g": 5, "h": {"i": 6}, "n": 5}}},
|
|
{"a": "z", "b": 3, "c": {"j": 7}},
|
|
{"a": "w", "b": 4, "c": {"k": 8, "f": {"g": 9, "n": {"o": 10, "p": 11}}}},
|
|
]
|
|
expected = STRUCTURE
|
|
|
|
actual = GenericDataFrameColumnParser.unique_json_structure(sample_data)
|
|
|
|
self.assertDictEqual(expected, actual)
|
|
|
|
def test_construct_column(self):
|
|
"""test construct column fn"""
|
|
expected = [
|
|
{
|
|
"dataTypeDisplay": "STRING",
|
|
"dataType": "STRING",
|
|
"name": "a",
|
|
"displayName": "a",
|
|
},
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "b",
|
|
"displayName": "b",
|
|
},
|
|
{
|
|
"dataTypeDisplay": "JSON",
|
|
"dataType": "JSON",
|
|
"name": "c",
|
|
"displayName": "c",
|
|
"children": [
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "d",
|
|
"displayName": "d",
|
|
},
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "e",
|
|
"displayName": "e",
|
|
},
|
|
{
|
|
"dataTypeDisplay": "JSON",
|
|
"dataType": "JSON",
|
|
"name": "f",
|
|
"displayName": "f",
|
|
"children": [
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "g",
|
|
"displayName": "g",
|
|
},
|
|
{
|
|
"dataTypeDisplay": "JSON",
|
|
"dataType": "JSON",
|
|
"name": "h",
|
|
"displayName": "h",
|
|
"children": [
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "i",
|
|
"displayName": "i",
|
|
}
|
|
],
|
|
},
|
|
{
|
|
"dataTypeDisplay": "JSON",
|
|
"dataType": "JSON",
|
|
"name": "n",
|
|
"displayName": "n",
|
|
"children": [
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "o",
|
|
"displayName": "o",
|
|
},
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "p",
|
|
"displayName": "p",
|
|
},
|
|
],
|
|
},
|
|
],
|
|
},
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "j",
|
|
"displayName": "j",
|
|
},
|
|
{
|
|
"dataTypeDisplay": "INT",
|
|
"dataType": "INT",
|
|
"name": "k",
|
|
"displayName": "k",
|
|
},
|
|
],
|
|
},
|
|
]
|
|
actual = GenericDataFrameColumnParser.construct_json_column_children(STRUCTURE)
|
|
|
|
for el in zip(expected, actual):
|
|
self.assertDictEqual(el[0], el[1])
|
|
|
|
def test_create_column_object(self):
|
|
"""test create column object fn"""
|
|
formatted_column = GenericDataFrameColumnParser.construct_json_column_children(
|
|
STRUCTURE
|
|
)
|
|
column = {
|
|
"dataTypeDisplay": "STRING",
|
|
"dataType": "STRING",
|
|
"name": "a",
|
|
"displayName": "a",
|
|
"children": formatted_column,
|
|
}
|
|
column_obj = Column(**column)
|
|
assert len(column_obj.children) == 3
|
|
|
|
|
|
class TestParquetDataFrameColumnParser(TestCase):
|
|
"""Test parquet dataframe column parser"""
|
|
|
|
@classmethod
|
|
def setUpClass(cls) -> None:
|
|
resources_path = os.path.join(
|
|
os.path.dirname(os.path.dirname(__file__)), "resources"
|
|
)
|
|
cls.parquet_path = os.path.join(resources_path, "datalake", "example.parquet")
|
|
|
|
cls.df = pd.read_parquet(cls.parquet_path)
|
|
|
|
cls.parquet_parser = ParquetDataFrameColumnParser(cls.df)
|
|
|
|
def test_parser_instantiation(self):
|
|
"""Test the right parser is instantiated from the creator method"""
|
|
parquet_parser = DataFrameColumnParser.create(self.df, SupportedTypes.PARQUET)
|
|
self.assertIsInstance(parquet_parser.parser, ParquetDataFrameColumnParser)
|
|
|
|
other_types = [typ for typ in SupportedTypes if typ != SupportedTypes.PARQUET]
|
|
for other_type in other_types:
|
|
with self.subTest(other_type=other_type):
|
|
generic_parser = DataFrameColumnParser.create(self.df, other_type)
|
|
self.assertIsInstance(
|
|
generic_parser.parser, GenericDataFrameColumnParser
|
|
)
|
|
|
|
def test_shuffle_and_sample_from_parser(self):
|
|
"""test the shuffle and sampling logic from the parser creator method"""
|
|
parquet_parser = DataFrameColumnParser.create(self.df, SupportedTypes.PARQUET)
|
|
self.assertEqual(parquet_parser.parser.data_frame.shape, self.df.shape)
|
|
|
|
parquet_parser = DataFrameColumnParser.create(
|
|
[self.df, self.df], SupportedTypes.PARQUET
|
|
)
|
|
self.assertEqual(parquet_parser.parser.data_frame.shape, self.df.shape)
|
|
|
|
parquet_parser = DataFrameColumnParser.create(
|
|
[self.df, self.df], SupportedTypes.PARQUET, sample=False
|
|
)
|
|
self.assertEqual(
|
|
parquet_parser.parser.data_frame.shape, pd.concat([self.df, self.df]).shape
|
|
)
|
|
|
|
def test_get_columns(self):
|
|
"""test `get_columns` method of the parquet column parser"""
|
|
expected = [
|
|
Column(
|
|
dataTypeDisplay="bool",
|
|
dataType=DataType.BOOLEAN,
|
|
name="a",
|
|
displayName="a",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="int8",
|
|
dataType=DataType.INT,
|
|
name="b",
|
|
displayName="b",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="int16",
|
|
dataType=DataType.INT,
|
|
name="c",
|
|
displayName="c",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="int32",
|
|
dataType=DataType.INT,
|
|
name="d",
|
|
displayName="d",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="int64",
|
|
dataType=DataType.INT,
|
|
name="e",
|
|
displayName="e",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="uint8",
|
|
dataType=DataType.UINT,
|
|
name="f",
|
|
displayName="f",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="uint16",
|
|
dataType=DataType.UINT,
|
|
name="g",
|
|
displayName="g",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="uint32",
|
|
dataType=DataType.UINT,
|
|
name="h",
|
|
displayName="h",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="uint64",
|
|
dataType=DataType.UINT,
|
|
name="i",
|
|
displayName="i",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="float",
|
|
dataType=DataType.FLOAT,
|
|
name="k",
|
|
displayName="k",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="double",
|
|
dataType=DataType.FLOAT,
|
|
name="l",
|
|
displayName="l",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="time64[us]",
|
|
dataType=DataType.DATETIME,
|
|
name="n",
|
|
displayName="n",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="timestamp[ns]",
|
|
dataType=DataType.DATETIME,
|
|
name="o",
|
|
displayName="o",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="date32[day]",
|
|
dataType=DataType.DATE,
|
|
name="p",
|
|
displayName="p",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="date32[day]",
|
|
dataType=DataType.DATE,
|
|
name="q",
|
|
displayName="q",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="duration[ns]",
|
|
dataType=DataType.INT,
|
|
name="r",
|
|
displayName="r",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="binary",
|
|
dataType=DataType.BINARY,
|
|
name="t",
|
|
displayName="t",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="string",
|
|
dataType=DataType.STRING,
|
|
name="u",
|
|
displayName="u",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="string",
|
|
dataType=DataType.STRING,
|
|
name="v",
|
|
displayName="v",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="binary",
|
|
dataType=DataType.BINARY,
|
|
name="w",
|
|
displayName="w",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="string",
|
|
dataType=DataType.STRING,
|
|
name="x",
|
|
displayName="x",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="string",
|
|
dataType=DataType.STRING,
|
|
name="y",
|
|
displayName="y",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="list<item: int64>",
|
|
dataType=DataType.ARRAY,
|
|
name="aa",
|
|
displayName="aa",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="list<item: int64>",
|
|
dataType=DataType.ARRAY,
|
|
name="bb",
|
|
displayName="bb",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="struct<ee: int64, ff: int64, gg: struct<hh: struct<ii: int64, jj: int64, kk: int64>>>",
|
|
dataType=DataType.STRUCT,
|
|
name="dd",
|
|
displayName="dd",
|
|
children=[
|
|
Column(
|
|
dataTypeDisplay="int64",
|
|
dataType=DataType.INT,
|
|
name="ee",
|
|
displayName="ee",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="int64",
|
|
dataType=DataType.INT,
|
|
name="ff",
|
|
displayName="ff",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="struct<hh: struct<ii: int64, jj: int64, kk: int64>>",
|
|
dataType=DataType.STRUCT,
|
|
name="gg",
|
|
displayName="gg",
|
|
children=[
|
|
Column(
|
|
dataTypeDisplay="struct<ii: int64, jj: int64, kk: int64>",
|
|
dataType=DataType.STRUCT,
|
|
name="hh",
|
|
displayName="hh",
|
|
children=[
|
|
Column(
|
|
dataTypeDisplay="int64",
|
|
dataType=DataType.INT,
|
|
name="ii",
|
|
displayName="ii",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="int64",
|
|
dataType=DataType.INT,
|
|
name="jj",
|
|
displayName="jj",
|
|
), # type: ignore
|
|
Column(
|
|
dataTypeDisplay="int64",
|
|
dataType=DataType.INT,
|
|
name="kk",
|
|
displayName="kk",
|
|
), # type: ignore
|
|
],
|
|
),
|
|
],
|
|
),
|
|
],
|
|
), # type: ignore
|
|
]
|
|
actual = self.parquet_parser.get_columns()
|
|
for validation in zip(expected, actual):
|
|
with self.subTest(validation=validation):
|
|
expected_col, actual_col = validation
|
|
self.assertEqual(expected_col.name, actual_col.name)
|
|
self.assertEqual(expected_col.displayName, actual_col.displayName)
|
|
self.assertEqual(expected_col.dataType, actual_col.dataType)
|
|
|
|
def _validate_parsed_column(self, expected, actual):
|
|
"""validate parsed column"""
|
|
self.assertEqual(expected.name, actual.name)
|
|
self.assertEqual(expected.dataType, actual.dataType)
|
|
self.assertEqual(expected.displayName, actual.displayName)
|
|
if expected.children:
|
|
self.assertEqual(len(expected.children), len(actual.children))
|
|
for validation in zip(expected.children, actual.children):
|
|
with self.subTest(validation=validation):
|
|
expected_col, actual_col = validation
|
|
self._validate_parsed_column(expected_col, actual_col)
|