import os
import logging
import sys
from pyflink.common import JsonRowDeserializationSchema, JsonRowSerializationSchema
from pyflink.common.typeinfo import Types
from pyflink.datastream.connectors import FlinkKafkaProducer, FlinkKafkaConsumer
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.table import TableEnvironment, EnvironmentSettings
def read_sql(file_path):
    if not os.path.isfile(file_path):
        raise TypeError(file_path + " does not exist")
    all_the_text = open(file_path).read()
    return all_the_text
def exec_sql():
    # 提交前修改sql路径
    # file_path = "/opt/client/Flink/flink/insertData2kafka.sql"
    # file_path = os.getcwd() + "/../../../../yarnship/insertData2kafka.sql"
    # file_path = "/opt/client/Flink/flink/conf/ssl/insertData2kafka.sql"
    file_path = "insertData2kafka.sql"
    sql = read_sql(file_path)
    t_env = TableEnvironment.create(EnvironmentSettings.in_streaming_mode())
    statement_set = t_env.create_statement_set()
    sqlArr = sql.split(";")
    for sqlStr in sqlArr:
        sqlStr = sqlStr.strip()
        if sqlStr.lower().startswith("create"):
            print("---------create---------------")
            print(sqlStr)
            t_env.execute_sql(sqlStr)
        if sqlStr.lower().startswith("insert"):
            print("---------insert---------------")
            print(sqlStr)
            statement_set.add_insert_sql(sqlStr)
    statement_set.execute()
def read_write_kafka():
    # find kafka connector jars
    env = StreamExecutionEnvironment.get_execution_environment()
    env.set_parallelism(1)
    specific_jars = "file:///opt/client/Flink/flink/lib/flink-connector-kafka-xxx.jar"
    # specific_jars = "file://" + os.getcwd() + "/../../../../yarnship/flink-connector-kafka-xxx.jar"
    # specific_jars = "file:///opt/client/Flink/flink/conf/ssl/flink-connector-kafka-xxx.jar"
    # the sql connector for kafka is used here as it's a fat jar and could avoid dependency issues
    env.add_jars(specific_jars)
    kafka_properties = {'bootstrap.servers': '192.168.20.162:21005', 'group.id': 'test_group'}
    deserialization_schema = JsonRowDeserializationSchema.builder() \
        .type_info(type_info=Types.ROW([Types.INT(), Types.STRING()])).build()
    kafka_consumer = FlinkKafkaConsumer(
        topics='test_source_topic',
        deserialization_schema=deserialization_schema,
        properties=kafka_properties)
    print("---------read ---------------")
    ds = env.add_source(kafka_consumer)
    serialization_schema = JsonRowSerializationSchema.builder().with_type_info(
        type_info=Types.ROW([Types.INT(), Types.STRING()])).build()
    kafka_producer = FlinkKafkaProducer(
        topic='test_sink_topic',
        serialization_schema=serialization_schema,
        producer_config=kafka_properties)
    print("--------write------------------")
    ds.add_sink(kafka_producer)
    env.execute("pyflink kafka test")
if __name__ == '__main__':
    logging.basicConfig(stream=sys.stdout, level=logging.INFO, format="%(message)s")
    print("------------------insert data to kafka----------------")
    exec_sql()
    print("------------------read_write_kafka----------------")
    read_write_kafka()

create table kafka_sink_table (
  age int,
  name varchar(10)
) with (
  'connector' = 'kafka',
  'topic' = 'test_source_topic', --写入Kafka的topic名称，需确保与上述Python文件中的topic相同
  'properties.bootstrap.servers' = 'Kafka的Broker实例业务IP:Kafka端口号',
  'properties.group.id' = 'test_group',
  'format' = 'json'
);
create TABLE datagen_source_table (
   age int,
  name varchar(10)
) WITH (
  'connector' = 'datagen',
  'rows-per-second' = '1'
);
INSERT INTO
  kafka_sink_table
SELECT
  *
FROM
  datagen_source_table;