pypaimon/pynative/tests/test_primary_key_reader.py

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import pyarrow as pa

from pypaimon.api import Schema
from pypaimon.pynative.tests import PypaimonTestBase


class NativeReaderTest(PypaimonTestBase):

    @classmethod
    def setUpClass(cls):
        super().setUpClass()
        cls.simple_pa_schema = pa.schema([
            ('user_id', pa.int64()),
            ('item_id', pa.int64()),
            ('behavior', pa.string()),
            ('dt', pa.string())
        ])
        cls.expected = pa.Table.from_pydict({
            'user_id': [1, 2, 3, 4, 5, 7, 8],
            'item_id': [1001, 1002, 1003, 1004, 1005, 1007, 1008],
            'behavior': ['a', 'b-new', 'c', None, 'e', 'g', 'h'],
            'dt': ['p1', 'p1', 'p2', 'p1', 'p2', 'p1', 'p2'],
        }, schema=cls.simple_pa_schema)

    def testPkParquetReader(self):
        schema = Schema(self.simple_pa_schema, partition_keys=['dt'], primary_keys=['user_id', 'dt'],
                        options={'bucket': '2'})
        self.catalog.create_table('default.test_pk_parquet', schema, False)
        j_table = self.catalog.get_table('default.test_pk_parquet')
        self._write_test_table(j_table)

        table = self.native_catalog.get_table("default.test_pk_parquet")
        read_builder = table.new_read_builder()
        actual = self._read_test_table(read_builder).sort_by('user_id')
        self.assertEqual(actual, self.expected)

    def testPkOrcReader(self):
        schema = Schema(self.simple_pa_schema, partition_keys=['dt'], primary_keys=['user_id', 'dt'], options={
            'bucket': '1',
            'file.format': 'orc'
        })
        self.catalog.create_table('default.test_pk_orc', schema, False)
        j_table = self.catalog.get_table('default.test_pk_orc')
        self._write_test_table(j_table)

        table = self.native_catalog.get_table("default.test_pk_orc")
        read_builder = table.new_read_builder()
        actual: pa.Table = self._read_test_table(read_builder).sort_by('user_id')

        # when bucket=1, actual field name will contain 'not null', so skip comparing field name
        for i in range(len(actual.columns)):
            col_a = actual.column(i)
            col_b = self.expected.column(i)
            self.assertEqual(col_a, col_b)

    def testPkAvroReader(self):
        schema = Schema(self.simple_pa_schema, partition_keys=['dt'], primary_keys=['user_id', 'dt'], options={
            'bucket': '2',
            'file.format': 'avro'
        })
        self.catalog.create_table('default.test_pk_avro', schema, False)
        j_table = self.catalog.get_table('default.test_pk_avro')
        self._write_test_table(j_table)

        table = self.native_catalog.get_table("default.test_pk_avro")
        read_builder = table.new_read_builder()
        actual = self._read_test_table(read_builder).sort_by('user_id')
        self.assertEqual(actual, self.expected)

    def testPkReaderWithFilter(self):
        schema = Schema(self.simple_pa_schema, partition_keys=['dt'], primary_keys=['user_id', 'dt'],
                        options={'bucket': '2'})
        self.catalog.create_table('default.test_pk_filter', schema, False)
        j_table = self.catalog.get_table('default.test_pk_filter')
        self._write_test_table(j_table)

        table = self.native_catalog.get_table("default.test_pk_filter")
        predicate_builder = table.new_read_builder().new_predicate_builder()
        p1 = predicate_builder.is_in('dt', ['p1'])
        p2 = predicate_builder.between('user_id', 2, 7)
        p3 = predicate_builder.is_not_null('behavior')
        g1 = predicate_builder.and_predicates([p1, p2, p3])
        read_builder = table.new_read_builder().with_filter(g1)
        actual = self._read_test_table(read_builder).sort_by('user_id')
        expected = pa.concat_tables([
            self.expected.slice(1, 1),  # 2/b
            self.expected.slice(5, 1)   # 7/g
        ])
        self.assertEqual(actual, expected)

    def testPkReaderWithProjection(self):
        schema = Schema(self.simple_pa_schema, partition_keys=['dt'], primary_keys=['user_id', 'dt'],
                        options={'bucket': '2'})
        self.catalog.create_table('default.test_pk_projection', schema, False)
        j_table = self.catalog.get_table('default.test_pk_projection')
        self._write_test_table(j_table)

        table = self.native_catalog.get_table("default.test_pk_projection")
        read_builder = table.new_read_builder().with_projection(['dt', 'user_id', 'behavior'])
        actual = self._read_test_table(read_builder).sort_by('user_id')
        expected = self.expected.select(['dt', 'user_id', 'behavior'])
        self.assertEqual(actual, expected)

    def _write_test_table(self, table):
        write_builder = table.new_batch_write_builder()

        table_write = write_builder.new_write()
        table_commit = write_builder.new_commit()
        data1 = {
            'user_id': [1, 2, 3, 4],
            'item_id': [1001, 1002, 1003, 1004],
            'behavior': ['a', 'b', 'c', None],
            'dt': ['p1', 'p1', 'p2', 'p1'],
        }
        pa_table = pa.Table.from_pydict(data1, schema=self.simple_pa_schema)
        table_write.write_arrow(pa_table)
        table_commit.commit(table_write.prepare_commit())
        table_write.close()
        table_commit.close()

        table_write = write_builder.new_write()
        table_commit = write_builder.new_commit()
        data1 = {
            'user_id': [5, 2, 7, 8],
            'item_id': [1005, 1002, 1007, 1008],
            'behavior': ['e', 'b-new', 'g', 'h'],
            'dt': ['p2', 'p1', 'p1', 'p2']
        }
        pa_table = pa.Table.from_pydict(data1, schema=self.simple_pa_schema)
        table_write.write_arrow(pa_table)
        table_commit.commit(table_write.prepare_commit())
        table_write.close()
        table_commit.close()

    def _read_test_table(self, read_builder):
        table_read = read_builder.new_read()
        splits = read_builder.new_scan().plan().splits()
        return table_read.to_arrow(splits)