98 lines
4.1 KiB
Python
98 lines
4.1 KiB
Python
# Copyright 2016 Hewlett Packard Enterprise Development Company LP
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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from pyspark.sql import SQLContext
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from monasca_transform.component import InstanceUsageDataAggParams
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from monasca_transform.component.setter import SetterComponent
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from monasca_transform.transform.transform_utils import InstanceUsageUtils
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import json
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class SetAggregatedMetricName(SetterComponent):
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"""setter component that sets final aggregated metric name.
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aggregated metric name is available as a parameter 'aggregated_metric_name'
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in aggregation_params in metric processing driver table.
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"""
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@staticmethod
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def _set_aggregated_metric_name(instance_usage_agg_params):
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row = instance_usage_agg_params.instance_usage_data
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agg_params = instance_usage_agg_params.agg_params
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try:
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processing_meta = row.processing_meta
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except AttributeError:
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processing_meta = {}
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# get any extra data
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extra_data_map = getattr(row, "extra_data_map", {})
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instance_usage_dict = {"tenant_id": row.tenant_id,
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"user_id": row.user_id,
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"resource_uuid": row.resource_uuid,
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"geolocation": row.geolocation,
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"region": row.region,
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"zone": row.zone,
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"host": row.host,
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"project_id": row.project_id,
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"aggregated_metric_name":
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agg_params["aggregated_metric_name"],
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"quantity": row.quantity,
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"firstrecord_timestamp_unix":
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row.firstrecord_timestamp_unix,
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"firstrecord_timestamp_string":
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row.firstrecord_timestamp_string,
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"lastrecord_timestamp_unix":
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row.lastrecord_timestamp_unix,
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"lastrecord_timestamp_string":
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row.lastrecord_timestamp_string,
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"record_count": row.record_count,
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"usage_date": row.usage_date,
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"usage_hour": row.usage_hour,
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"usage_minute": row.usage_minute,
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"aggregation_period": row.aggregation_period,
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"processing_meta": processing_meta,
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"extra_data_map": extra_data_map}
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instance_usage_data_json = json.dumps(instance_usage_dict)
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return instance_usage_data_json
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@staticmethod
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def setter(transform_context, instance_usage_df):
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"""set the aggregated metric name field for elements in instance usage rdd"""
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transform_spec_df = transform_context.transform_spec_df_info
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agg_params = transform_spec_df.select(
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"aggregation_params_map.aggregated_metric_name").collect()[0].\
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asDict()
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instance_usage_df_agg_params = instance_usage_df.rdd.map(
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lambda x: InstanceUsageDataAggParams(x, agg_params))
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instance_usage_json_rdd = instance_usage_df_agg_params.map(
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SetAggregatedMetricName._set_aggregated_metric_name)
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sql_context = SQLContext.getOrCreate(instance_usage_df.rdd.context)
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instance_usage_trans_df = InstanceUsageUtils.create_df_from_json_rdd(
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sql_context,
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instance_usage_json_rdd)
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return instance_usage_trans_df
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