def word_count(input_path, output_path):
env = StreamExecutionEnvironment.get_execution_environment()
env.set_runtime_mode(RuntimeExecutionMode.BATCH)
# write all the data to one file
env.set_parallelism(1)
# define the source
if input_path is not None:
ds = env.from_source(
source=FileSource.for_record_stream_format(StreamFormat.text_line_format(),
input_path)
.process_static_file_set().build(),
watermark_strategy=WatermarkStrategy.for_monotonous_timestamps(),
source_name="file_source"
)
else:
print("Executing word_count example with default input data set.")
print("Use --input to specify file input.")
ds = env.from_collection(word_count_data)
def split(line):
yield from line.split()
# compute word count
ds = ds.flat_map(split) \
.map(lambda i: (i, 1), output_type=Types.TUPLE([Types.STRING(), Types.INT()])) \
.key_by(lambda i: i[0]) \
.reduce(lambda i, j: (i[0], i[1] + j[1]))
# define the sink
if output_path is not None:
ds.sink_to(
sink=FileSink.for_row_format(
base_path=output_path,
encoder=Encoder.simple_string_encoder())
.with_output_file_config(
OutputFileConfig.builder()
.with_part_prefix("prefix")
.with_part_suffix(".ext")
.build())
.with_rolling_policy(RollingPolicy.default_rolling_policy())
.build()
)
else:
print("Printing result to stdout. Use --output to specify output path.")
ds.print()
# submit for execution
env.execute()
help='Output file to write results to.')
argv = sys.argv[1:]
known_args, _ = parser.parse_known_args(argv)
output_path = known_args.output
env = StreamExecutionEnvironment.get_execution_environment()
# write all the data to one file
env.set_parallelism(1)
# define the source
data_stream = env.from_collection([('hi', 1), ('hi', 2), ('hi', 3),
('hi', 4), ('hi', 5), ('hi', 8),
('hi', 9), ('hi', 15)],
type_info=Types.TUPLE(
[Types.STRING(),
Types.INT()]))
# define the watermark strategy
watermark_strategy = WatermarkStrategy.for_monotonous_timestamps() \
.with_timestamp_assigner(MyTimestampAssigner())
ds = data_stream.assign_timestamps_and_watermarks(watermark_strategy) \
.key_by(lambda x: x[0], key_type=Types.STRING()) \
.window(TumblingEventTimeWindows.of(Time.milliseconds(5))) \
.process(CountWindowProcessFunction(),
Types.TUPLE([Types.STRING(), Types.INT(), Types.INT(), Types.INT()]))
# define the sink
if output_path is not None:
ds.sink_to(sink=FileSink.for_row_format(
dest='output',
required=False,
help='Output file to write results to.')
argv = sys.argv[1:]
known_args, _ = parser.parse_known_args(argv)
output_path = known_args.output
env = StreamExecutionEnvironment.get_execution_environment()
# write all the data to one file
env.set_parallelism(1)
# define the source
data_stream = env.from_collection([
(1, 'hi'), (2, 'hello'), (3, 'hi'), (4, 'hello'), (5, 'hi'), (6, 'hello'), (6, 'hello')],
type_info=Types.TUPLE([Types.INT(), Types.STRING()]))
ds = data_stream.key_by(lambda x: x[1], key_type=Types.STRING()) \
.count_window(2) \
.apply(SumWindowFunction(), Types.TUPLE([Types.STRING(), Types.INT()]))
# define the sink
if output_path is not None:
ds.sink_to(
sink=FileSink.for_row_format(
base_path=output_path,
encoder=Encoder.simple_string_encoder())
.with_output_file_config(
OutputFileConfig.builder()
.with_part_prefix("prefix")
.with_part_suffix(".ext")