Source code for airflow.contrib.sensors.cassandra_record_sensor

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from airflow.contrib.hooks.cassandra_hook import CassandraHook
from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.utils.decorators import apply_defaults


[docs]class CassandraRecordSensor(BaseSensorOperator):
    """
    Checks for the existence of a record in a Cassandra cluster.

    For example, if you want to wait for a record that has values 'v1' and 'v2' for each
    primary keys 'p1' and 'p2' to be populated in keyspace 'k' and table 't',
    instantiate it as follows:

    >>> cassandra_sensor = CassandraRecordSensor(table="k.t",
    ...                                          keys={"p1": "v1", "p2": "v2"},
    ...                                          cassandra_conn_id="cassandra_default",
    ...                                          task_id="cassandra_sensor")
    """
[docs]    template_fields = ('table', 'keys')

    @apply_defaults
    def __init__(self, table, keys, cassandra_conn_id, *args, **kwargs):
        """
        Create a new CassandraRecordSensor

        :param table: Target Cassandra table.
                      Use dot notation to target a specific keyspace.
        :type table: str
        :param keys: The keys and their values to be monitored
        :type keys: dict
        :param cassandra_conn_id: The connection ID to use
                                  when connecting to Cassandra cluster
        :type cassandra_conn_id: str
        """
        super(CassandraRecordSensor, self).__init__(*args, **kwargs)
        self.cassandra_conn_id = cassandra_conn_id
        self.table = table
        self.keys = keys

[docs]    def poke(self, context):
        self.log.info('Sensor check existence of record: %s', self.keys)
        hook = CassandraHook(self.cassandra_conn_id)
        return hook.record_exists(self.table, self.keys)