monasca-analytics/monasca_analytics/source/kafka.py

100 lines
3.4 KiB
Python

#!/usr/bin/env python
# Copyright (c) 2016 Hewlett Packard Enterprise Development Company, L.P.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import logging
from pyspark.streaming import kafka
import voluptuous
import monasca_analytics.banana.typeck.type_util as type_util
import monasca_analytics.component.params as params
from monasca_analytics.source import base
from monasca_analytics.util import validation_utils as vu
logger = logging.getLogger(__name__)
class KafkaSource(base.BaseSource):
"""A Kafka source implementation that consumes data from a Kafka queue."""
@staticmethod
def validate_config(_config):
source_schema = voluptuous.Schema({
"module": voluptuous.And(basestring, vu.NoSpaceCharacter()),
"params": {
"zk_host": voluptuous.And(basestring, vu.NoSpaceCharacter()),
"zk_port": int,
"group_id": voluptuous.And(basestring, vu.NoSpaceCharacter()),
"topics": {
voluptuous.And(basestring, vu.NoSpaceCharacter()):
voluptuous.And(int, voluptuous.Range(min=1))
}
}
}, required=True)
return source_schema(_config)
@staticmethod
def get_default_config():
return {
"module": KafkaSource.__name__,
"params": {
"zk_host": "localhost",
"zk_port": 2181,
"group_id": "my_group_id",
"topics": {
"my_topic": 1
}
}
}
@staticmethod
def get_params():
return [
params.ParamDescriptor('zk_host', type_util.String(),
'localhost'),
params.ParamDescriptor('zk_port', type_util.Number(),
2181),
params.ParamDescriptor('group_id', type_util.String(),
'my_group_id'),
params.ParamDescriptor('topics',
type_util.Object(strict_checking=False))
]
def create_dstream(self, ssc):
"""Dstream creation
The _dstream object is created before this source is bound
to the consumers. It uses a KafkaUtils.createStream, to read data from
the Kafka queue that was defined in the configuration.
:type ssc: pyspark.streaming.StreamingContext
:param ssc: Spark Streaming Context
"""
return kafka.KafkaUtils.createStream(
ssc,
"{0}:{1}".format(
self._config["params"]["zk_host"],
self._config["params"]["zk_port"]),
self._config["params"]["group_id"],
self._config["params"]["topics"])
def terminate_source(self):
pass
def get_feature_list(self):
raise NotImplementedError("This method needs to be implemented")