import json
import logging

from pyflink.common import Types, Row
from pyflink.common.typeinfo import RowTypeInfo
from pyflink.datastream import FlatMapFunction
from pyflink.datastream.connectors.jdbc import JdbcSink, JdbcConnectionOptions, JdbcExecutionOptions
from pyflink.table.sources

logger = logging.getLogger(__name__)


class TraceIDMapToTupleFlatMap(FlatMapFunction):
    def flat_map(self, value):
        try:
            m = json.loads(value.traces)
        except json.JSONDecodeError as de:
            logger.warning(f'decode trace value:{value.traces} failed:{de}')
            return []
        return [Row(f0=trace_id, f1=timestamp) for trace_id, timestamp in m.items()]


class ClickhouseSink:
    def __init__(self, ch_host, ch_port, ch_user, ch_name, ch_password):
        exec_ops = JdbcExecutionOptions.builder().with_batch_size(1000).with_max_retries(3).build()
        conn_ops = (JdbcConnectionOptions.JdbcConnectionOptionsBuilder()
                    .with_url(f"jdbc:clickhouse://{ch_host}:{ch_port}/{ch_name}")
                    .with_user_name(ch_user)
                    .with_password(ch_password)
                    .build())
        sql = 'insert into sample_hit_trace (trace_id, timestamp) values(?, ?)'
        # type_info = Types.ROW([Types.STRING(), Types.SQL_TIMESTAMP()])
        type_info = RowTypeInfo([Types.STRING(), Types.LONG()], ['f0', 'f1'])
        self.__ch = JdbcSink.sink(sql, type_info, conn_ops, exec_ops)

    @property
    def ch_sink(self):
        return self.__ch