Source code for airflow.contrib.sensors.cassandra_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: >>> CassandraRecordSensor(table="k.t", keys={"p1": "v1", "p2": "v2"}, ... cassandra_conn_id="cassandra_default", task_id="cassandra_sensor") <Task(CassandraRecordSensor): cassandra_sensor> """ 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: string :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: string """ super(CassandraRecordSensor, self).__init__(*args, **kwargs) self.cassandra_conn_id = cassandra_conn_id self.table = table self.keys = keys
[docs] def poke(self, context):'Sensor check existence of record: %s', self.keys) hook = CassandraHook(self.cassandra_conn_id) return hook.record_exists(self.table, self.keys)