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[ | |
{ | |
"clientId": "5998b748-652b-47d5-8b41-2bf8b244357c", | |
"id": "ecb6d957-3dd4-47ec-ae3b-56618d11c170", | |
"environment": { | |
"profile": { | |
"resetDate": 16581, | |
"creationDate": 16319 | |
}, | |
"settings": { |
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from moztelemetry.dataset import Dataset | |
# Let's start selecting the `telemetry` dataset. | |
# This will load all the metadata about available dimensions and file locations. | |
dataset = Dataset.from_source('telemetry') | |
#The list of dimensions is now available on the `schema` attribute. | |
assert dataset.schema == [ | |
u'submissionDate', | |
u'sourceName', |
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#!/usr/bin/pyspark | |
import logging | |
from os import environ | |
from mozaggregator.aggregator import aggregate_metrics | |
from mozaggregator.db import submit_aggregates | |
from pyspark import SparkContext, SparkConf | |
conf = SparkConf().setAppName('telemetry-aggregates') |
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#!/bin/bash | |
conda install psycopg2 --yes | |
git clone https://github.com/maurodoglio/bz2db.git | |
pip install -r bz2db/requirements.txt | |
cd bz2db | |
python update_bugs.py |
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dataset = Dataset.from_source('telemetry) | |
filtered_dataset = dataset.where(docType='main', | |
submissionDate=lambda x: x.startswith('20160701')) | |
pings = filtered_dataset.records(sc, sample=0.1) |
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from moztelemetry import get_pings | |
pings = get_pings(sc, doc_type='OTHER', submission_date='20160714').filter(lambda x: x['meta']['docType'] == 'sync') | |
first_ping = pings.take(1) |
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