def test_collect_for_all_data_types(self): expected_result = [Row(1, None, 1, True, 32767, -2147483648, 1.23, 1.98932, bytearray(b'pyflink'), 'pyflink', datetime.date(2014, 9, 13), datetime.time(12, 0), datetime.datetime(2018, 3, 11, 3, 0, 0, 123000), [Row(['[pyflink]']), Row(['[pyflink]']), Row(['[pyflink]'])], {1: Row(['[flink]']), 2: Row(['[pyflink]'])}, decimal.Decimal('1000000000000000000.05'), decimal.Decimal( '1000000000000000000.05999999999999999899999999999'))] source = self.t_env.from_elements([(1, None, 1, True, 32767, -2147483648, 1.23, 1.98932, bytearray(b'pyflink'), 'pyflink', datetime.date(2014, 9, 13), datetime.time(hour=12, minute=0, second=0, microsecond=123000), datetime.datetime(2018, 3, 11, 3, 0, 0, 123000), [Row(['pyflink']), Row(['pyflink']), Row(['pyflink'])], {1: Row(['flink']), 2: Row(['pyflink'])}, decimal.Decimal('1000000000000000000.05'), decimal.Decimal( '1000000000000000000.0599999999999999989' '9999999999'))], DataTypes.ROW([DataTypes.FIELD("a", DataTypes.BIGINT()), DataTypes.FIELD("b", DataTypes.BIGINT()), DataTypes.FIELD("c", DataTypes.TINYINT()), DataTypes.FIELD("d", DataTypes.BOOLEAN()), DataTypes.FIELD("e", DataTypes.SMALLINT()), DataTypes.FIELD("f", DataTypes.INT()), DataTypes.FIELD("g", DataTypes.FLOAT()), DataTypes.FIELD("h", DataTypes.DOUBLE()), DataTypes.FIELD("i", DataTypes.BYTES()), DataTypes.FIELD("j", DataTypes.STRING()), DataTypes.FIELD("k", DataTypes.DATE()), DataTypes.FIELD("l", DataTypes.TIME()), DataTypes.FIELD("m", DataTypes.TIMESTAMP(3)), DataTypes.FIELD("n", DataTypes.ARRAY( DataTypes.ROW([DataTypes.FIELD('ss2', DataTypes.STRING())]))), DataTypes.FIELD("o", DataTypes.MAP( DataTypes.BIGINT(), DataTypes.ROW( [DataTypes.FIELD('ss', DataTypes.STRING())]))), DataTypes.FIELD("p", DataTypes.DECIMAL(38, 18)), DataTypes.FIELD("q", DataTypes.DECIMAL(38, 18))])) table_result = source.execute() with table_result.collect() as result: collected_result = [] for i in result: collected_result.append(i) self.assertEqual(expected_result, collected_result)
def _create_csv_primitive_column_schema_and_lines( ) -> Tuple[CsvSchema, List[str]]: schema = CsvSchema.builder() \ .add_number_column('tinyint', DataTypes.TINYINT()) \ .add_number_column('smallint', DataTypes.SMALLINT()) \ .add_number_column('int', DataTypes.INT()) \ .add_number_column('bigint', DataTypes.BIGINT()) \ .add_number_column('float', DataTypes.FLOAT()) \ .add_number_column('double', DataTypes.DOUBLE()) \ .add_number_column('decimal', DataTypes.DECIMAL(2, 0)) \ .add_boolean_column('boolean') \ .add_string_column('string') \ .build() lines = [ '127,' '-32767,' '2147483647,' '-9223372036854775808,' '3e38,' '2e-308,' '1.5,' 'true,' 'string\n', ] return schema, lines
def test_from_element(self): t_env = self.t_env field_names = [ "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s" ] field_types = [ DataTypes.BIGINT(), DataTypes.DOUBLE(), DataTypes.STRING(), DataTypes.STRING(), DataTypes.DATE(), DataTypes.TIME(), DataTypes.TIMESTAMP(), DataTypes.TIMESTAMP_WITH_LOCAL_TIME_ZONE(), DataTypes.INTERVAL(DataTypes.DAY(), DataTypes.SECOND()), DataTypes.ARRAY(DataTypes.DOUBLE()), DataTypes.ARRAY(DataTypes.DOUBLE(False)), DataTypes.ARRAY(DataTypes.STRING()), DataTypes.ARRAY(DataTypes.DATE()), DataTypes.DECIMAL(10, 0), DataTypes.ROW([ DataTypes.FIELD("a", DataTypes.BIGINT()), DataTypes.FIELD("b", DataTypes.DOUBLE()) ]), DataTypes.MAP(DataTypes.STRING(), DataTypes.DOUBLE()), DataTypes.BYTES(), ExamplePointUDT(), PythonOnlyUDT() ] schema = DataTypes.ROW( list( map( lambda field_name, field_type: DataTypes.FIELD( field_name, field_type), field_names, field_types))) table_sink = source_sink_utils.TestAppendSink(field_names, field_types) t_env.register_table_sink("Results", table_sink) t = t_env.from_elements( [(1, 1.0, "hi", "hello", datetime.date(1970, 1, 2), datetime.time(1, 0, 0), datetime.datetime( 1970, 1, 2, 0, 0), datetime.datetime(1970, 1, 2, 0, 0), datetime.timedelta(days=1, microseconds=10), [1.0, None], array.array("d", [1.0, 2.0]), ["abc"], [datetime.date(1970, 1, 2)], Decimal(1), Row("a", "b")(1, 2.0), { "key": 1.0 }, bytearray(b'ABCD'), ExamplePoint( 1.0, 2.0), PythonOnlyPoint(3.0, 4.0))], schema) t.insert_into("Results") self.env.execute() actual = source_sink_utils.results() expected = [ '1,1.0,hi,hello,1970-01-02,01:00:00,1970-01-02 00:00:00.0,' '1970-01-02 00:00:00.0,86400000010,[1.0, null],[1.0, 2.0],[abc],[1970-01-02],' '1,1,2.0,{key=1.0},[65, 66, 67, 68],[1.0, 2.0],[3.0, 4.0]' ] self.assert_equals(actual, expected)
def test_blink_from_element(self): t_env = BatchTableEnvironment.create( environment_settings=EnvironmentSettings.new_instance( ).use_blink_planner().in_batch_mode().build()) field_names = [ "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q" ] field_types = [ DataTypes.BIGINT(), DataTypes.DOUBLE(), DataTypes.STRING(), DataTypes.STRING(), DataTypes.DATE(), DataTypes.TIME(), DataTypes.TIMESTAMP(3), DataTypes.INTERVAL(DataTypes.SECOND(3)), DataTypes.ARRAY(DataTypes.DOUBLE()), DataTypes.ARRAY(DataTypes.DOUBLE(False)), DataTypes.ARRAY(DataTypes.STRING()), DataTypes.ARRAY(DataTypes.DATE()), DataTypes.DECIMAL(38, 18), DataTypes.ROW([ DataTypes.FIELD("a", DataTypes.BIGINT()), DataTypes.FIELD("b", DataTypes.DOUBLE()) ]), DataTypes.MAP(DataTypes.STRING(), DataTypes.DOUBLE()), DataTypes.BYTES(), PythonOnlyUDT() ] schema = DataTypes.ROW( list( map( lambda field_name, field_type: DataTypes.FIELD( field_name, field_type), field_names, field_types))) table_sink = source_sink_utils.TestAppendSink(field_names, field_types) t_env.register_table_sink("Results", table_sink) t = t_env.from_elements( [(1, 1.0, "hi", "hello", datetime.date(1970, 1, 2), datetime.time(1, 0, 0), datetime.datetime(1970, 1, 2, 0, 0), datetime.timedelta(days=1, microseconds=10), [1.0, None], array.array("d", [1.0, 2.0]), ["abc"], [datetime.date(1970, 1, 2)], Decimal(1), Row("a", "b")(1, 2.0), { "key": 1.0 }, bytearray(b'ABCD'), PythonOnlyPoint(3.0, 4.0))], schema) t.insert_into("Results") t_env.execute("test") actual = source_sink_utils.results() expected = [ '1,1.0,hi,hello,1970-01-02,01:00:00,1970-01-02 00:00:00.0,' '86400000,[1.0, null],[1.0, 2.0],[abc],[1970-01-02],' '1.000000000000000000,1,2.0,{key=1.0},[65, 66, 67, 68],[3.0, 4.0]' ] self.assert_equals(actual, expected)
def test_from_element(self): t_env = self.t_env a = array.array('b') a.fromstring('ABCD') t = t_env.from_elements([ (1, 1.0, "hi", "hello", datetime.date(1970, 1, 2), datetime.time(1, 0, 0), datetime.datetime(1970, 1, 2, 0, 0), [1.0, None], array.array("d", [1.0, 2.0]), ["abc"], [datetime.date(1970, 1, 2)], Decimal(1), Row("a", "b")(1, 2.0), { "key": 1.0 }, a, ExamplePoint(1.0, 2.0), PythonOnlyPoint(3.0, 4.0)) ]) field_names = [ "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q" ] field_types = [ DataTypes.BIGINT(), DataTypes.DOUBLE(), DataTypes.STRING(), DataTypes.STRING(), DataTypes.DATE(), DataTypes.TIME(), DataTypes.TIMESTAMP(), DataTypes.ARRAY(DataTypes.DOUBLE()), DataTypes.ARRAY(DataTypes.DOUBLE(False)), DataTypes.ARRAY(DataTypes.STRING()), DataTypes.ARRAY(DataTypes.DATE()), DataTypes.DECIMAL(), DataTypes.ROW([ DataTypes.FIELD("a", DataTypes.BIGINT()), DataTypes.FIELD("b", DataTypes.DOUBLE()) ]), DataTypes.MAP(DataTypes.VARCHAR(), DataTypes.DOUBLE()), DataTypes.VARBINARY(), ExamplePointUDT(), PythonOnlyUDT() ] t_env.register_table_sink("Results", field_names, field_types, source_sink_utils.TestAppendSink()) t.insert_into("Results") t_env.exec_env().execute() actual = source_sink_utils.results() expected = [ '1,1.0,hi,hello,1970-01-02,01:00:00,1970-01-02 00:00:00.0,[1.0, null],' '[1.0, 2.0],[abc],[1970-01-02],1,1,2.0,{key=1.0},[65, 66, 67, 68],[1.0, 2.0],' '[3.0, 4.0]' ] self.assert_equals(actual, expected)
def test_all_data_types(self): import pandas as pd import numpy as np @udf(result_type=DataTypes.TINYINT(), func_type="pandas") def tinyint_func(tinyint_param): assert isinstance(tinyint_param, pd.Series) assert isinstance(tinyint_param[0], np.int8), \ 'tinyint_param of wrong type %s !' % type(tinyint_param[0]) return tinyint_param @udf(result_type=DataTypes.SMALLINT(), func_type="pandas") def smallint_func(smallint_param): assert isinstance(smallint_param, pd.Series) assert isinstance(smallint_param[0], np.int16), \ 'smallint_param of wrong type %s !' % type(smallint_param[0]) assert smallint_param[ 0] == 32767, 'smallint_param of wrong value %s' % smallint_param return smallint_param @udf(result_type=DataTypes.INT(), func_type="pandas") def int_func(int_param): assert isinstance(int_param, pd.Series) assert isinstance(int_param[0], np.int32), \ 'int_param of wrong type %s !' % type(int_param[0]) assert int_param[ 0] == -2147483648, 'int_param of wrong value %s' % int_param return int_param @udf(result_type=DataTypes.BIGINT(), func_type="pandas") def bigint_func(bigint_param): assert isinstance(bigint_param, pd.Series) assert isinstance(bigint_param[0], np.int64), \ 'bigint_param of wrong type %s !' % type(bigint_param[0]) return bigint_param @udf(result_type=DataTypes.BOOLEAN(), func_type="pandas") def boolean_func(boolean_param): assert isinstance(boolean_param, pd.Series) assert isinstance(boolean_param[0], np.bool_), \ 'boolean_param of wrong type %s !' % type(boolean_param[0]) return boolean_param @udf(result_type=DataTypes.FLOAT(), func_type="pandas") def float_func(float_param): assert isinstance(float_param, pd.Series) assert isinstance(float_param[0], np.float32), \ 'float_param of wrong type %s !' % type(float_param[0]) return float_param @udf(result_type=DataTypes.DOUBLE(), func_type="pandas") def double_func(double_param): assert isinstance(double_param, pd.Series) assert isinstance(double_param[0], np.float64), \ 'double_param of wrong type %s !' % type(double_param[0]) return double_param @udf(result_type=DataTypes.STRING(), func_type="pandas") def varchar_func(varchar_param): assert isinstance(varchar_param, pd.Series) assert isinstance(varchar_param[0], str), \ 'varchar_param of wrong type %s !' % type(varchar_param[0]) return varchar_param @udf(result_type=DataTypes.BYTES(), func_type="pandas") def varbinary_func(varbinary_param): assert isinstance(varbinary_param, pd.Series) assert isinstance(varbinary_param[0], bytes), \ 'varbinary_param of wrong type %s !' % type(varbinary_param[0]) return varbinary_param @udf(result_type=DataTypes.DECIMAL(38, 18), func_type="pandas") def decimal_func(decimal_param): assert isinstance(decimal_param, pd.Series) assert isinstance(decimal_param[0], decimal.Decimal), \ 'decimal_param of wrong type %s !' % type(decimal_param[0]) return decimal_param @udf(result_type=DataTypes.DATE(), func_type="pandas") def date_func(date_param): assert isinstance(date_param, pd.Series) assert isinstance(date_param[0], datetime.date), \ 'date_param of wrong type %s !' % type(date_param[0]) return date_param @udf(result_type=DataTypes.TIME(), func_type="pandas") def time_func(time_param): assert isinstance(time_param, pd.Series) assert isinstance(time_param[0], datetime.time), \ 'time_param of wrong type %s !' % type(time_param[0]) return time_param timestamp_value = datetime.datetime(1970, 1, 2, 0, 0, 0, 123000) @udf(result_type=DataTypes.TIMESTAMP(3), func_type="pandas") def timestamp_func(timestamp_param): assert isinstance(timestamp_param, pd.Series) assert isinstance(timestamp_param[0], datetime.datetime), \ 'timestamp_param of wrong type %s !' % type(timestamp_param[0]) assert timestamp_param[0] == timestamp_value, \ 'timestamp_param is wrong value %s, should be %s!' % (timestamp_param[0], timestamp_value) return timestamp_param def array_func(array_param): assert isinstance(array_param, pd.Series) assert isinstance(array_param[0], np.ndarray), \ 'array_param of wrong type %s !' % type(array_param[0]) return array_param array_str_func = udf(array_func, result_type=DataTypes.ARRAY(DataTypes.STRING()), func_type="pandas") array_timestamp_func = udf(array_func, result_type=DataTypes.ARRAY( DataTypes.TIMESTAMP(3)), func_type="pandas") array_int_func = udf(array_func, result_type=DataTypes.ARRAY(DataTypes.INT()), func_type="pandas") @udf(result_type=DataTypes.ARRAY(DataTypes.STRING()), func_type="pandas") def nested_array_func(nested_array_param): assert isinstance(nested_array_param, pd.Series) assert isinstance(nested_array_param[0], np.ndarray), \ 'nested_array_param of wrong type %s !' % type(nested_array_param[0]) return pd.Series(nested_array_param[0]) row_type = DataTypes.ROW([ DataTypes.FIELD("f1", DataTypes.INT()), DataTypes.FIELD("f2", DataTypes.STRING()), DataTypes.FIELD("f3", DataTypes.TIMESTAMP(3)), DataTypes.FIELD("f4", DataTypes.ARRAY(DataTypes.INT())) ]) @udf(result_type=row_type, func_type="pandas") def row_func(row_param): assert isinstance(row_param, pd.DataFrame) assert isinstance(row_param.f1, pd.Series) assert isinstance(row_param.f1[0], np.int32), \ 'row_param.f1 of wrong type %s !' % type(row_param.f1[0]) assert isinstance(row_param.f2, pd.Series) assert isinstance(row_param.f2[0], str), \ 'row_param.f2 of wrong type %s !' % type(row_param.f2[0]) assert isinstance(row_param.f3, pd.Series) assert isinstance(row_param.f3[0], datetime.datetime), \ 'row_param.f3 of wrong type %s !' % type(row_param.f3[0]) assert isinstance(row_param.f4, pd.Series) assert isinstance(row_param.f4[0], np.ndarray), \ 'row_param.f4 of wrong type %s !' % type(row_param.f4[0]) return row_param table_sink = source_sink_utils.TestAppendSink([ 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u' ], [ DataTypes.TINYINT(), DataTypes.SMALLINT(), DataTypes.INT(), DataTypes.BIGINT(), DataTypes.BOOLEAN(), DataTypes.BOOLEAN(), DataTypes.FLOAT(), DataTypes.DOUBLE(), DataTypes.STRING(), DataTypes.STRING(), DataTypes.BYTES(), DataTypes.DECIMAL(38, 18), DataTypes.DECIMAL(38, 18), DataTypes.DATE(), DataTypes.TIME(), DataTypes.TIMESTAMP(3), DataTypes.ARRAY(DataTypes.STRING()), DataTypes.ARRAY(DataTypes.TIMESTAMP(3)), DataTypes.ARRAY(DataTypes.INT()), DataTypes.ARRAY(DataTypes.STRING()), row_type ]) self.t_env.register_table_sink("Results", table_sink) t = self.t_env.from_elements( [(1, 32767, -2147483648, 1, True, False, 1.0, 1.0, 'hello', '中文', bytearray(b'flink'), decimal.Decimal('1000000000000000000.05'), decimal.Decimal( '1000000000000000000.05999999999999999899999999999'), datetime.date(2014, 9, 13), datetime.time(hour=1, minute=0, second=1), timestamp_value, ['hello', '中文', None], [timestamp_value], [1, 2], [[ 'hello', '中文', None ]], Row(1, 'hello', timestamp_value, [1, 2]))], DataTypes.ROW([ DataTypes.FIELD("a", DataTypes.TINYINT()), DataTypes.FIELD("b", DataTypes.SMALLINT()), DataTypes.FIELD("c", DataTypes.INT()), DataTypes.FIELD("d", DataTypes.BIGINT()), DataTypes.FIELD("e", DataTypes.BOOLEAN()), DataTypes.FIELD("f", DataTypes.BOOLEAN()), DataTypes.FIELD("g", DataTypes.FLOAT()), DataTypes.FIELD("h", DataTypes.DOUBLE()), DataTypes.FIELD("i", DataTypes.STRING()), DataTypes.FIELD("j", DataTypes.STRING()), DataTypes.FIELD("k", DataTypes.BYTES()), DataTypes.FIELD("l", DataTypes.DECIMAL(38, 18)), DataTypes.FIELD("m", DataTypes.DECIMAL(38, 18)), DataTypes.FIELD("n", DataTypes.DATE()), DataTypes.FIELD("o", DataTypes.TIME()), DataTypes.FIELD("p", DataTypes.TIMESTAMP(3)), DataTypes.FIELD("q", DataTypes.ARRAY(DataTypes.STRING())), DataTypes.FIELD("r", DataTypes.ARRAY(DataTypes.TIMESTAMP(3))), DataTypes.FIELD("s", DataTypes.ARRAY(DataTypes.INT())), DataTypes.FIELD( "t", DataTypes.ARRAY(DataTypes.ARRAY(DataTypes.STRING()))), DataTypes.FIELD("u", row_type) ])) t.select( tinyint_func(t.a), smallint_func(t.b), int_func(t.c), bigint_func(t.d), boolean_func(t.e), boolean_func(t.f), float_func(t.g), double_func(t.h), varchar_func(t.i), varchar_func(t.j), varbinary_func(t.k), decimal_func(t.l), decimal_func(t.m), date_func(t.n), time_func(t.o), timestamp_func(t.p), array_str_func(t.q), array_timestamp_func(t.r), array_int_func(t.s), nested_array_func(t.t), row_func(t.u)) \ .execute_insert("Results").wait() actual = source_sink_utils.results() self.assert_equals(actual, [ "+I[1, 32767, -2147483648, 1, true, false, 1.0, 1.0, hello, 中文, " "[102, 108, 105, 110, 107], 1000000000000000000.050000000000000000, " "1000000000000000000.059999999999999999, 2014-09-13, 01:00:01, " "1970-01-02 00:00:00.123, [hello, 中文, null], [1970-01-02 00:00:00.123], " "[1, 2], [hello, 中文, null], +I[1, hello, 1970-01-02 00:00:00.123, [1, 2]]]" ])
def test_all_data_types(self): def boolean_func(bool_param): assert isinstance(bool_param, bool), 'bool_param of wrong type %s !' \ % type(bool_param) return bool_param def tinyint_func(tinyint_param): assert isinstance(tinyint_param, int), 'tinyint_param of wrong type %s !' \ % type(tinyint_param) return tinyint_param def smallint_func(smallint_param): assert isinstance(smallint_param, int), 'smallint_param of wrong type %s !' \ % type(smallint_param) assert smallint_param == 32767, 'smallint_param of wrong value %s' % smallint_param return smallint_param def int_func(int_param): assert isinstance(int_param, int), 'int_param of wrong type %s !' \ % type(int_param) assert int_param == -2147483648, 'int_param of wrong value %s' % int_param return int_param def bigint_func(bigint_param): assert isinstance(bigint_param, int), 'bigint_param of wrong type %s !' \ % type(bigint_param) return bigint_param def bigint_func_none(bigint_param): assert bigint_param is None, 'bigint_param %s should be None!' % bigint_param return bigint_param def float_func(float_param): assert isinstance(float_param, float) and float_equal(float_param, 1.23, 1e-6), \ 'float_param is wrong value %s !' % float_param return float_param def double_func(double_param): assert isinstance(double_param, float) and float_equal(double_param, 1.98932, 1e-7), \ 'double_param is wrong value %s !' % double_param return double_param def bytes_func(bytes_param): assert bytes_param == b'flink', \ 'bytes_param is wrong value %s !' % bytes_param return bytes_param def str_func(str_param): assert str_param == 'pyflink', \ 'str_param is wrong value %s !' % str_param return str_param def date_func(date_param): from datetime import date assert date_param == date(year=2014, month=9, day=13), \ 'date_param is wrong value %s !' % date_param return date_param def time_func(time_param): from datetime import time assert time_param == time(hour=12, minute=0, second=0, microsecond=123000), \ 'time_param is wrong value %s !' % time_param return time_param def timestamp_func(timestamp_param): from datetime import datetime assert timestamp_param == datetime(2018, 3, 11, 3, 0, 0, 123000), \ 'timestamp_param is wrong value %s !' % timestamp_param return timestamp_param def array_func(array_param): assert array_param == [[1, 2, 3]], \ 'array_param is wrong value %s !' % array_param return array_param[0] def map_func(map_param): assert map_param == {1: 'flink', 2: 'pyflink'}, \ 'map_param is wrong value %s !' % map_param return map_param def decimal_func(decimal_param): from decimal import Decimal assert decimal_param == Decimal('1000000000000000000.050000000000000000'), \ 'decimal_param is wrong value %s !' % decimal_param return decimal_param def decimal_cut_func(decimal_param): from decimal import Decimal assert decimal_param == Decimal('1000000000000000000.059999999999999999'), \ 'decimal_param is wrong value %s !' % decimal_param return decimal_param self.t_env.create_temporary_system_function( "boolean_func", udf(boolean_func, result_type=DataTypes.BOOLEAN())) self.t_env.create_temporary_system_function( "tinyint_func", udf(tinyint_func, result_type=DataTypes.TINYINT())) self.t_env.create_temporary_system_function( "smallint_func", udf(smallint_func, result_type=DataTypes.SMALLINT())) self.t_env.create_temporary_system_function( "int_func", udf(int_func, result_type=DataTypes.INT())) self.t_env.create_temporary_system_function( "bigint_func", udf(bigint_func, result_type=DataTypes.BIGINT())) self.t_env.create_temporary_system_function( "bigint_func_none", udf(bigint_func_none, result_type=DataTypes.BIGINT())) self.t_env.create_temporary_system_function( "float_func", udf(float_func, result_type=DataTypes.FLOAT())) self.t_env.create_temporary_system_function( "double_func", udf(double_func, result_type=DataTypes.DOUBLE())) self.t_env.create_temporary_system_function( "bytes_func", udf(bytes_func, result_type=DataTypes.BYTES())) self.t_env.create_temporary_system_function( "str_func", udf(str_func, result_type=DataTypes.STRING())) self.t_env.create_temporary_system_function( "date_func", udf(date_func, result_type=DataTypes.DATE())) self.t_env.create_temporary_system_function( "time_func", udf(time_func, result_type=DataTypes.TIME())) self.t_env.create_temporary_system_function( "timestamp_func", udf(timestamp_func, result_type=DataTypes.TIMESTAMP(3))) self.t_env.create_temporary_system_function( "array_func", udf(array_func, result_type=DataTypes.ARRAY(DataTypes.BIGINT()))) self.t_env.create_temporary_system_function( "map_func", udf(map_func, result_type=DataTypes.MAP(DataTypes.BIGINT(), DataTypes.STRING()))) self.t_env.register_function( "decimal_func", udf(decimal_func, result_type=DataTypes.DECIMAL(38, 18))) self.t_env.register_function( "decimal_cut_func", udf(decimal_cut_func, result_type=DataTypes.DECIMAL(38, 18))) table_sink = source_sink_utils.TestAppendSink([ 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q' ], [ DataTypes.BIGINT(), DataTypes.BIGINT(), DataTypes.TINYINT(), DataTypes.BOOLEAN(), DataTypes.SMALLINT(), DataTypes.INT(), DataTypes.FLOAT(), DataTypes.DOUBLE(), DataTypes.BYTES(), DataTypes.STRING(), DataTypes.DATE(), DataTypes.TIME(), DataTypes.TIMESTAMP(3), DataTypes.ARRAY(DataTypes.BIGINT()), DataTypes.MAP(DataTypes.BIGINT(), DataTypes.STRING()), DataTypes.DECIMAL(38, 18), DataTypes.DECIMAL(38, 18) ]) self.t_env.register_table_sink("Results", table_sink) import datetime import decimal t = self.t_env.from_elements( [(1, None, 1, True, 32767, -2147483648, 1.23, 1.98932, bytearray(b'flink'), 'pyflink', datetime.date(2014, 9, 13), datetime.time(hour=12, minute=0, second=0, microsecond=123000), datetime.datetime(2018, 3, 11, 3, 0, 0, 123000), [[1, 2, 3]], { 1: 'flink', 2: 'pyflink' }, decimal.Decimal('1000000000000000000.05'), decimal.Decimal( '1000000000000000000.05999999999999999899999999999'))], DataTypes.ROW([ DataTypes.FIELD("a", DataTypes.BIGINT()), DataTypes.FIELD("b", DataTypes.BIGINT()), DataTypes.FIELD("c", DataTypes.TINYINT()), DataTypes.FIELD("d", DataTypes.BOOLEAN()), DataTypes.FIELD("e", DataTypes.SMALLINT()), DataTypes.FIELD("f", DataTypes.INT()), DataTypes.FIELD("g", DataTypes.FLOAT()), DataTypes.FIELD("h", DataTypes.DOUBLE()), DataTypes.FIELD("i", DataTypes.BYTES()), DataTypes.FIELD("j", DataTypes.STRING()), DataTypes.FIELD("k", DataTypes.DATE()), DataTypes.FIELD("l", DataTypes.TIME()), DataTypes.FIELD("m", DataTypes.TIMESTAMP(3)), DataTypes.FIELD( "n", DataTypes.ARRAY(DataTypes.ARRAY(DataTypes.BIGINT()))), DataTypes.FIELD( "o", DataTypes.MAP(DataTypes.BIGINT(), DataTypes.STRING())), DataTypes.FIELD("p", DataTypes.DECIMAL(38, 18)), DataTypes.FIELD("q", DataTypes.DECIMAL(38, 18)) ])) exec_insert_table( t.select("bigint_func(a), bigint_func_none(b)," "tinyint_func(c), boolean_func(d)," "smallint_func(e),int_func(f)," "float_func(g),double_func(h)," "bytes_func(i),str_func(j)," "date_func(k),time_func(l)," "timestamp_func(m),array_func(n)," "map_func(o),decimal_func(p)," "decimal_cut_func(q)"), "Results") actual = source_sink_utils.results() # Currently the sink result precision of DataTypes.TIME(precision) only supports 0. self.assert_equals(actual, [ "1,null,1,true,32767,-2147483648,1.23,1.98932," "[102, 108, 105, 110, 107],pyflink,2014-09-13," "12:00:00,2018-03-11 03:00:00.123,[1, 2, 3]," "{1=flink, 2=pyflink},1000000000000000000.050000000000000000," "1000000000000000000.059999999999999999" ])
def test_udf_with_constant_params(self): def udf_with_constant_params(p, null_param, tinyint_param, smallint_param, int_param, bigint_param, decimal_param, float_param, double_param, boolean_param, str_param, date_param, time_param, timestamp_param): from decimal import Decimal import datetime assert null_param is None, 'null_param is wrong value %s' % null_param assert isinstance(tinyint_param, int), 'tinyint_param of wrong type %s !' \ % type(tinyint_param) p += tinyint_param assert isinstance(smallint_param, int), 'smallint_param of wrong type %s !' \ % type(smallint_param) p += smallint_param assert isinstance(int_param, int), 'int_param of wrong type %s !' \ % type(int_param) p += int_param assert isinstance(bigint_param, int), 'bigint_param of wrong type %s !' \ % type(bigint_param) p += bigint_param assert decimal_param == Decimal('1.05'), \ 'decimal_param is wrong value %s ' % decimal_param p += int(decimal_param) assert isinstance(float_param, float) and float_equal(float_param, 1.23, 1e-06), \ 'float_param is wrong value %s ' % float_param p += int(float_param) assert isinstance(double_param, float) and float_equal(double_param, 1.98932, 1e-07), \ 'double_param is wrong value %s ' % double_param p += int(double_param) assert boolean_param is True, 'boolean_param is wrong value %s' % boolean_param assert str_param == 'flink', 'str_param is wrong value %s' % str_param assert date_param == datetime.date(year=2014, month=9, day=13), \ 'date_param is wrong value %s' % date_param assert time_param == datetime.time(hour=12, minute=0, second=0), \ 'time_param is wrong value %s' % time_param assert timestamp_param == datetime.datetime(1999, 9, 10, 5, 20, 10), \ 'timestamp_param is wrong value %s' % timestamp_param return p self.t_env.register_function( "udf_with_constant_params", udf(udf_with_constant_params, input_types=[ DataTypes.BIGINT(), DataTypes.BIGINT(), DataTypes.TINYINT(), DataTypes.SMALLINT(), DataTypes.INT(), DataTypes.BIGINT(), DataTypes.DECIMAL(38, 18), DataTypes.FLOAT(), DataTypes.DOUBLE(), DataTypes.BOOLEAN(), DataTypes.STRING(), DataTypes.DATE(), DataTypes.TIME(), DataTypes.TIMESTAMP(3) ], result_type=DataTypes.BIGINT())) self.t_env.register_function( "udf_with_all_constant_params", udf(lambda i, j: i + j, [DataTypes.BIGINT(), DataTypes.BIGINT()], DataTypes.BIGINT())) table_sink = source_sink_utils.TestAppendSink( ['a', 'b'], [DataTypes.BIGINT(), DataTypes.BIGINT()]) self.t_env.register_table_sink("Results", table_sink) t = self.t_env.from_elements([(1, 2, 3), (2, 5, 6), (3, 1, 9)], ['a', 'b', 'c']) self.t_env.register_table("test_table", t) self.t_env.sql_query("select udf_with_all_constant_params(" "cast (1 as BIGINT)," "cast (2 as BIGINT)), " "udf_with_constant_params(a, " "cast (null as BIGINT)," "cast (1 as TINYINT)," "cast (1 as SMALLINT)," "cast (1 as INT)," "cast (1 as BIGINT)," "cast (1.05 as DECIMAL)," "cast (1.23 as FLOAT)," "cast (1.98932 as DOUBLE)," "true," "'flink'," "cast ('2014-09-13' as DATE)," "cast ('12:00:00' as TIME)," "cast ('1999-9-10 05:20:10' as TIMESTAMP))" " from test_table").insert_into("Results") self.t_env.execute("test") actual = source_sink_utils.results() self.assert_equals(actual, ["3,8", "3,9", "3,10"])
from pyflink.datastream import StreamExecutionEnvironment from pyflink.table import StreamTableEnvironment, DataTypes from pyflink.table.descriptors import Schema, OldCsv, FileSystem from pyflink.table.udf import udf import numpy as np from sklearn.linear_model import LinearRegression as LR from sklearn.preprocessing import PolynomialFeatures from sklearn.model_selection import train_test_split env = StreamExecutionEnvironment.get_execution_environment() env.set_parallelism(1) t_env = StreamTableEnvironment.create(env) @udf(input_types=[DataTypes.DECIMAL(38, 12, nullable=True)], result_type=DataTypes.DECIMAL(38, 12, nullable=True)) def myadd(i): return i * i * 2 # add = udf(myadd, [DataTypes.BIGINT(), DataTypes.BIGINT()], DataTypes.BIGINT()) t_env.register_function("add", myadd) t_env.connect(FileSystem().path('/tmp/input')) \ .with_format(OldCsv() .field('b', DataTypes.DECIMAL(38,12,nullable=True))) \ .with_schema(Schema() .field('b', DataTypes.DECIMAL(38,12,nullable=True))) \ .create_temporary_table('mySource')
def test_all_data_types(self): import pandas as pd import numpy as np def tinyint_func(tinyint_param): assert isinstance(tinyint_param, pd.Series) assert isinstance(tinyint_param[0], np.int8), \ 'tinyint_param of wrong type %s !' % type(tinyint_param[0]) return tinyint_param def smallint_func(smallint_param): assert isinstance(smallint_param, pd.Series) assert isinstance(smallint_param[0], np.int16), \ 'smallint_param of wrong type %s !' % type(smallint_param[0]) assert smallint_param[ 0] == 32767, 'smallint_param of wrong value %s' % smallint_param return smallint_param def int_func(int_param): assert isinstance(int_param, pd.Series) assert isinstance(int_param[0], np.int32), \ 'int_param of wrong type %s !' % type(int_param[0]) assert int_param[ 0] == -2147483648, 'int_param of wrong value %s' % int_param return int_param def bigint_func(bigint_param): assert isinstance(bigint_param, pd.Series) assert isinstance(bigint_param[0], np.int64), \ 'bigint_param of wrong type %s !' % type(bigint_param[0]) return bigint_param def boolean_func(boolean_param): assert isinstance(boolean_param, pd.Series) assert isinstance(boolean_param[0], np.bool_), \ 'boolean_param of wrong type %s !' % type(boolean_param[0]) return boolean_param def float_func(float_param): assert isinstance(float_param, pd.Series) assert isinstance(float_param[0], np.float32), \ 'float_param of wrong type %s !' % type(float_param[0]) return float_param def double_func(double_param): assert isinstance(double_param, pd.Series) assert isinstance(double_param[0], np.float64), \ 'double_param of wrong type %s !' % type(double_param[0]) return double_param def varchar_func(varchar_param): assert isinstance(varchar_param, pd.Series) assert isinstance(varchar_param[0], str), \ 'varchar_param of wrong type %s !' % type(varchar_param[0]) return varchar_param def varbinary_func(varbinary_param): assert isinstance(varbinary_param, pd.Series) assert isinstance(varbinary_param[0], bytes), \ 'varbinary_param of wrong type %s !' % type(varbinary_param[0]) return varbinary_param def decimal_func(decimal_param): assert isinstance(decimal_param, pd.Series) assert isinstance(decimal_param[0], decimal.Decimal), \ 'decimal_param of wrong type %s !' % type(decimal_param[0]) return decimal_param def date_func(date_param): assert isinstance(date_param, pd.Series) assert isinstance(date_param[0], datetime.date), \ 'date_param of wrong type %s !' % type(date_param[0]) return date_param def time_func(time_param): assert isinstance(time_param, pd.Series) assert isinstance(time_param[0], datetime.time), \ 'time_param of wrong type %s !' % type(time_param[0]) return time_param timestamp_value = datetime.datetime(1970, 1, 1, 0, 0, 0, 123000) def timestamp_func(timestamp_param): assert isinstance(timestamp_param, pd.Series) assert isinstance(timestamp_param[0], datetime.datetime), \ 'timestamp_param of wrong type %s !' % type(timestamp_param[0]) assert timestamp_param[0] == timestamp_value, \ 'timestamp_param is wrong value %s, should be %s!' % (timestamp_param[0], timestamp_value) return timestamp_param self.t_env.register_function( "tinyint_func", udf(tinyint_func, [DataTypes.TINYINT()], DataTypes.TINYINT(), udf_type="pandas")) self.t_env.register_function( "smallint_func", udf(smallint_func, [DataTypes.SMALLINT()], DataTypes.SMALLINT(), udf_type="pandas")) self.t_env.register_function( "int_func", udf(int_func, [DataTypes.INT()], DataTypes.INT(), udf_type="pandas")) self.t_env.register_function( "bigint_func", udf(bigint_func, [DataTypes.BIGINT()], DataTypes.BIGINT(), udf_type="pandas")) self.t_env.register_function( "boolean_func", udf(boolean_func, [DataTypes.BOOLEAN()], DataTypes.BOOLEAN(), udf_type="pandas")) self.t_env.register_function( "float_func", udf(float_func, [DataTypes.FLOAT()], DataTypes.FLOAT(), udf_type="pandas")) self.t_env.register_function( "double_func", udf(double_func, [DataTypes.DOUBLE()], DataTypes.DOUBLE(), udf_type="pandas")) self.t_env.register_function( "varchar_func", udf(varchar_func, [DataTypes.STRING()], DataTypes.STRING(), udf_type="pandas")) self.t_env.register_function( "varbinary_func", udf(varbinary_func, [DataTypes.BYTES()], DataTypes.BYTES(), udf_type="pandas")) self.t_env.register_function( "decimal_func", udf(decimal_func, [DataTypes.DECIMAL(38, 18)], DataTypes.DECIMAL(38, 18), udf_type="pandas")) self.t_env.register_function( "date_func", udf(date_func, [DataTypes.DATE()], DataTypes.DATE(), udf_type="pandas")) self.t_env.register_function( "time_func", udf(time_func, [DataTypes.TIME()], DataTypes.TIME(), udf_type="pandas")) self.t_env.register_function( "timestamp_func", udf(timestamp_func, [DataTypes.TIMESTAMP(3)], DataTypes.TIMESTAMP(3), udf_type="pandas")) table_sink = source_sink_utils.TestAppendSink([ 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p' ], [ DataTypes.TINYINT(), DataTypes.SMALLINT(), DataTypes.INT(), DataTypes.BIGINT(), DataTypes.BOOLEAN(), DataTypes.BOOLEAN(), DataTypes.FLOAT(), DataTypes.DOUBLE(), DataTypes.STRING(), DataTypes.STRING(), DataTypes.BYTES(), DataTypes.DECIMAL(38, 18), DataTypes.DECIMAL(38, 18), DataTypes.DATE(), DataTypes.TIME(), DataTypes.TIMESTAMP(3) ]) self.t_env.register_table_sink("Results", table_sink) t = self.t_env.from_elements( [(1, 32767, -2147483648, 1, True, False, 1.0, 1.0, 'hello', '中文', bytearray(b'flink'), decimal.Decimal('1000000000000000000.05'), decimal.Decimal( '1000000000000000000.05999999999999999899999999999'), datetime.date(2014, 9, 13), datetime.time(hour=1, minute=0, second=1), timestamp_value)], DataTypes.ROW([ DataTypes.FIELD("a", DataTypes.TINYINT()), DataTypes.FIELD("b", DataTypes.SMALLINT()), DataTypes.FIELD("c", DataTypes.INT()), DataTypes.FIELD("d", DataTypes.BIGINT()), DataTypes.FIELD("e", DataTypes.BOOLEAN()), DataTypes.FIELD("f", DataTypes.BOOLEAN()), DataTypes.FIELD("g", DataTypes.FLOAT()), DataTypes.FIELD("h", DataTypes.DOUBLE()), DataTypes.FIELD("i", DataTypes.STRING()), DataTypes.FIELD("j", DataTypes.STRING()), DataTypes.FIELD("k", DataTypes.BYTES()), DataTypes.FIELD("l", DataTypes.DECIMAL(38, 18)), DataTypes.FIELD("m", DataTypes.DECIMAL(38, 18)), DataTypes.FIELD("n", DataTypes.DATE()), DataTypes.FIELD("o", DataTypes.TIME()), DataTypes.FIELD("p", DataTypes.TIMESTAMP(3)) ])) t.select("tinyint_func(a)," "smallint_func(b)," "int_func(c)," "bigint_func(d)," "boolean_func(e)," "boolean_func(f)," "float_func(g)," "double_func(h)," "varchar_func(i)," "varchar_func(j)," "varbinary_func(k)," "decimal_func(l)," "decimal_func(m)," "date_func(n)," "time_func(o)," "timestamp_func(p)") \ .insert_into("Results") self.t_env.execute("test") actual = source_sink_utils.results() self.assert_equals(actual, [ "1,32767,-2147483648,1,true,false,1.0,1.0,hello,中文," "[102, 108, 105, 110, 107],1000000000000000000.050000000000000000," "1000000000000000000.059999999999999999,2014-09-13,01:00:01," "1970-01-01 00:00:00.123" ])
if __name__ == '__main__': # stream setting s_env = StreamExecutionEnvironment.get_execution_environment() s_env.set_parallelism(1) s_env.set_stream_time_characteristic(TimeCharacteristic.EventTime) st_env = StreamTableEnvironment.create(s_env) # csv path for csv sink result_file = "/tmp/tumble_time_window_streaming.csv" if os.path.exists(result_file): os.remove(result_file) # udf @udf(input_types=[DataTypes.DECIMAL(38, 12, nullable=True)], result_type=DataTypes.DECIMAL(38, 12, nullable=True)) def myadd(i): return i * i * 2 st_env.register_function("add", myadd) # way kafka st_env \ .connect( # declare the external system to connect to Kafka() .version("universal") .topic("user") # .start_from_earliest() # .start_from_earliest() .start_from_specific_offset(0,496) .property("zookeeper.connect", "6.86.2.170:2181") .property("bootstrap.servers", "6.86.2.170:9092")
def test_from_element(self): t_env = self.t_env field_names = [ "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q" ] field_types = [ DataTypes.BIGINT(), DataTypes.DOUBLE(), DataTypes.STRING(), DataTypes.STRING(), DataTypes.DATE(), DataTypes.TIME(), DataTypes.TIMESTAMP(3), DataTypes.INTERVAL(DataTypes.SECOND(3)), DataTypes.ARRAY(DataTypes.DOUBLE()), DataTypes.ARRAY(DataTypes.DOUBLE(False)), DataTypes.ARRAY(DataTypes.STRING()), DataTypes.ARRAY(DataTypes.DATE()), DataTypes.DECIMAL(38, 18), DataTypes.ROW([ DataTypes.FIELD("a", DataTypes.BIGINT()), DataTypes.FIELD("b", DataTypes.DOUBLE()) ]), DataTypes.MAP(DataTypes.STRING(), DataTypes.DOUBLE()), DataTypes.BYTES(), PythonOnlyUDT() ] schema = DataTypes.ROW( list( map( lambda field_name, field_type: DataTypes.FIELD( field_name, field_type), field_names, field_types))) sink_table_ddl = """ CREATE TABLE Results( a BIGINT, b DOUBLE, c STRING, d STRING, e DATE, f TIME, g TIMESTAMP(3), h INT, i ARRAY<DOUBLE>, j ARRAY<DOUBLE NOT NULL>, k ARRAY<STRING>, l ARRAY<DATE>, m DECIMAL(38, 18), n ROW<a BIGINT, b DOUBLE>, o MAP<STRING, DOUBLE>, p BYTES, q ARRAY<DOUBLE NOT NULL>) WITH ('connector'='test-sink') """ self.t_env.execute_sql(sink_table_ddl) t = t_env.from_elements( [(1, 1.0, "hi", "hello", datetime.date(1970, 1, 2), datetime.time(1, 0, 0), datetime.datetime(1970, 1, 2, 0, 0), datetime.timedelta(days=1, microseconds=10), [1.0, None], array.array("d", [1.0, 2.0]), ["abc"], [datetime.date(1970, 1, 2)], Decimal(1), Row("a", "b")(1, 2.0), { "key": 1.0 }, bytearray(b'ABCD'), PythonOnlyPoint(3.0, 4.0))], schema) t.execute_insert("Results").wait() actual = source_sink_utils.results() expected = [ '+I[1, 1.0, hi, hello, 1970-01-02, 01:00, 1970-01-02T00:00, ' '86400, [1.0, null], [1.0, 2.0], [abc], [1970-01-02], ' '1.000000000000000000, +I[1, 2.0], {key=1.0}, [65, 66, 67, 68], [3.0, 4.0]]' ] self.assert_equals(actual, expected)
def test_all_data_types(self): def boolean_func(bool_param): assert isinstance(bool_param, bool), 'bool_param of wrong type %s !' \ % type(bool_param) return bool_param def tinyint_func(tinyint_param): assert isinstance(tinyint_param, int), 'tinyint_param of wrong type %s !' \ % type(tinyint_param) return tinyint_param def smallint_func(smallint_param): assert isinstance(smallint_param, int), 'smallint_param of wrong type %s !' \ % type(smallint_param) assert smallint_param == 32767, 'smallint_param of wrong value %s' % smallint_param return smallint_param def int_func(int_param): assert isinstance(int_param, int), 'int_param of wrong type %s !' \ % type(int_param) assert int_param == -2147483648, 'int_param of wrong value %s' % int_param return int_param def bigint_func(bigint_param): assert isinstance(bigint_param, int), 'bigint_param of wrong type %s !' \ % type(bigint_param) return bigint_param def bigint_func_none(bigint_param): assert bigint_param is None, 'bigint_param %s should be None!' % bigint_param return bigint_param def float_func(float_param): assert isinstance(float_param, float) and float_equal(float_param, 1.23, 1e-6), \ 'float_param is wrong value %s !' % float_param return float_param def double_func(double_param): assert isinstance(double_param, float) and float_equal(double_param, 1.98932, 1e-7), \ 'double_param is wrong value %s !' % double_param return double_param def bytes_func(bytes_param): assert bytes_param == b'flink', \ 'bytes_param is wrong value %s !' % bytes_param return bytes_param def str_func(str_param): assert str_param == 'pyflink', \ 'str_param is wrong value %s !' % str_param return str_param def date_func(date_param): from datetime import date assert date_param == date(year=2014, month=9, day=13), \ 'date_param is wrong value %s !' % date_param return date_param def time_func(time_param): from datetime import time assert time_param == time(hour=12, minute=0, second=0, microsecond=123000), \ 'time_param is wrong value %s !' % time_param return time_param def timestamp_func(timestamp_param): from datetime import datetime assert timestamp_param == datetime(2018, 3, 11, 3, 0, 0, 123000), \ 'timestamp_param is wrong value %s !' % timestamp_param return timestamp_param def array_func(array_param): assert array_param == [[1, 2, 3]] or array_param == ((1, 2, 3),), \ 'array_param is wrong value %s !' % array_param return array_param[0] def map_func(map_param): assert map_param == {1: 'flink', 2: 'pyflink'}, \ 'map_param is wrong value %s !' % map_param return map_param def decimal_func(decimal_param): from decimal import Decimal assert decimal_param == Decimal('1000000000000000000.050000000000000000'), \ 'decimal_param is wrong value %s !' % decimal_param return decimal_param def decimal_cut_func(decimal_param): from decimal import Decimal assert decimal_param == Decimal('1000000000000000000.059999999999999999'), \ 'decimal_param is wrong value %s !' % decimal_param return decimal_param self.t_env.create_temporary_system_function( "boolean_func", udf(boolean_func, result_type=DataTypes.BOOLEAN())) self.t_env.create_temporary_system_function( "tinyint_func", udf(tinyint_func, result_type=DataTypes.TINYINT())) self.t_env.create_temporary_system_function( "smallint_func", udf(smallint_func, result_type=DataTypes.SMALLINT())) self.t_env.create_temporary_system_function( "int_func", udf(int_func, result_type=DataTypes.INT())) self.t_env.create_temporary_system_function( "bigint_func", udf(bigint_func, result_type=DataTypes.BIGINT())) self.t_env.create_temporary_system_function( "bigint_func_none", udf(bigint_func_none, result_type=DataTypes.BIGINT())) self.t_env.create_temporary_system_function( "float_func", udf(float_func, result_type=DataTypes.FLOAT())) self.t_env.create_temporary_system_function( "double_func", udf(double_func, result_type=DataTypes.DOUBLE())) self.t_env.create_temporary_system_function( "bytes_func", udf(bytes_func, result_type=DataTypes.BYTES())) self.t_env.create_temporary_system_function( "str_func", udf(str_func, result_type=DataTypes.STRING())) self.t_env.create_temporary_system_function( "date_func", udf(date_func, result_type=DataTypes.DATE())) self.t_env.create_temporary_system_function( "time_func", udf(time_func, result_type=DataTypes.TIME())) self.t_env.create_temporary_system_function( "timestamp_func", udf(timestamp_func, result_type=DataTypes.TIMESTAMP(3))) self.t_env.create_temporary_system_function( "array_func", udf(array_func, result_type=DataTypes.ARRAY(DataTypes.BIGINT()))) self.t_env.create_temporary_system_function( "map_func", udf(map_func, result_type=DataTypes.MAP(DataTypes.BIGINT(), DataTypes.STRING()))) self.t_env.register_function( "decimal_func", udf(decimal_func, result_type=DataTypes.DECIMAL(38, 18))) self.t_env.register_function( "decimal_cut_func", udf(decimal_cut_func, result_type=DataTypes.DECIMAL(38, 18))) sink_table_ddl = """ CREATE TABLE Results( a BIGINT, b BIGINT, c TINYINT, d BOOLEAN, e SMALLINT, f INT, g FLOAT, h DOUBLE, i BYTES, j STRING, k DATE, l TIME, m TIMESTAMP(3), n ARRAY<BIGINT>, o MAP<BIGINT, STRING>, p DECIMAL(38, 18), q DECIMAL(38, 18)) WITH ('connector'='test-sink') """ self.t_env.execute_sql(sink_table_ddl) import datetime import decimal t = self.t_env.from_elements( [(1, None, 1, True, 32767, -2147483648, 1.23, 1.98932, bytearray(b'flink'), 'pyflink', datetime.date(2014, 9, 13), datetime.time(hour=12, minute=0, second=0, microsecond=123000), datetime.datetime(2018, 3, 11, 3, 0, 0, 123000), [[1, 2, 3]], { 1: 'flink', 2: 'pyflink' }, decimal.Decimal('1000000000000000000.05'), decimal.Decimal( '1000000000000000000.05999999999999999899999999999'))], DataTypes.ROW([ DataTypes.FIELD("a", DataTypes.BIGINT()), DataTypes.FIELD("b", DataTypes.BIGINT()), DataTypes.FIELD("c", DataTypes.TINYINT()), DataTypes.FIELD("d", DataTypes.BOOLEAN()), DataTypes.FIELD("e", DataTypes.SMALLINT()), DataTypes.FIELD("f", DataTypes.INT()), DataTypes.FIELD("g", DataTypes.FLOAT()), DataTypes.FIELD("h", DataTypes.DOUBLE()), DataTypes.FIELD("i", DataTypes.BYTES()), DataTypes.FIELD("j", DataTypes.STRING()), DataTypes.FIELD("k", DataTypes.DATE()), DataTypes.FIELD("l", DataTypes.TIME()), DataTypes.FIELD("m", DataTypes.TIMESTAMP(3)), DataTypes.FIELD( "n", DataTypes.ARRAY(DataTypes.ARRAY(DataTypes.BIGINT()))), DataTypes.FIELD( "o", DataTypes.MAP(DataTypes.BIGINT(), DataTypes.STRING())), DataTypes.FIELD("p", DataTypes.DECIMAL(38, 18)), DataTypes.FIELD("q", DataTypes.DECIMAL(38, 18)) ])) t.select(call("bigint_func", t.a), call("bigint_func_none", t.b), call("tinyint_func", t.c), call("boolean_func", t.d), call("smallint_func", t.e), call("int_func", t.f), call("float_func", t.g), call("double_func", t.h), call("bytes_func", t.i), call("str_func", t.j), call("date_func", t.k), call("time_func", t.l), call("timestamp_func", t.m), call("array_func", t.n), call("map_func", t.o), call("decimal_func", t.p), call("decimal_cut_func", t.q)) \ .execute_insert("Results").wait() actual = source_sink_utils.results() # Currently the sink result precision of DataTypes.TIME(precision) only supports 0. self.assert_equals(actual, [ "+I[1, null, 1, true, 32767, -2147483648, 1.23, 1.98932, " "[102, 108, 105, 110, 107], pyflink, 2014-09-13, " "12:00:00.123, 2018-03-11T03:00:00.123, [1, 2, 3], " "{1=flink, 2=pyflink}, 1000000000000000000.050000000000000000, " "1000000000000000000.059999999999999999]" ])