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cron: | |
- description: "Run scheduled tasks" | |
url: /tasks/schedule | |
schedule: every 60 minutes synchronized | |
target: zorya-backend |
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"""Admin view """ | |
import flask_admin | |
from flask_admin.contrib import appengine | |
from wtforms import validators | |
from collections import OrderedDict | |
from validators import GreaterEqualThan, SmallerEqualThan | |
class LastUpdatedOrderedDict(OrderedDict): | |
"""Store items in the order the keys were last added""" |
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def calc_slope(self, minuets): | |
""" | |
Calculate the slope of available memory change. | |
:param: minuets how long to go back in time | |
""" | |
met = metrics.Metrics(self.cluster_name) | |
series = met.read_timeseries('YARNMemoryAvailablePercentage', minuets) | |
retlist = [] |
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def calc_how_many(self): | |
""" | |
Calculate how many new nodes of each type we need. | |
:return: | |
""" | |
# No allocated memory so we don't need any workers above the | |
# bare minimum | |
if self.scale_to != -1: | |
self.total = self.min_instances |
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@app.route('/tasks/check-load') | |
def check_load(): | |
"""Entry point for cron task that launches a task for each cluster | |
check cluster stats""" | |
clusters = settings.get_all_clusters_settings() | |
for cluster in clusters.iter(): | |
task = taskqueue.add(queue_name='shamash', | |
url="/monitors", | |
method='GET', | |
params={'cluster_name': cluster.Cluster}) |
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cron: | |
- description: "check cluster load" | |
url: /tasks/check-load | |
schedule: every 2 minutes |
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def get_tf_record(sentence): | |
global words | |
# tokenize the pattern | |
sentence_words = nltk.word_tokenize(sentence) | |
# stem each word | |
sentence_words = [stemmer.stem(word.lower()) for word in sentence_words] | |
# bag of words | |
bow = [0]*len(words) | |
for s in sentence_words: | |
for i, w in enumerate(words): |
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# shuffle our features and turn into np.array as tensorflow takes in numpy array | |
random.shuffle(training) | |
training = np.array(training) | |
# trainX contains the Bag of words and train_y contains the label/ category | |
train_x = list(training[:, 0]) | |
train_y = list(training[:, 1]) | |
# reset underlying graph data | |
tf.reset_default_graph() |
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SELECT review ,(communication+price+wait+quality) as score | |
FROM [[aviv-playground:telegrass_reviews.reviews] | |
WHERE RAND() < 0.7 |
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city | population | unique_reviewers | ratio | |
---|---|---|---|---|
Tel Aviv | 438818 | 3783 | 0.8620886107680177 | |
Givatayim | 58508 | 424 | 0.7246872222602038 | |
Bat Yam | 128904 | 761 | 0.5903618196487308 | |
Ramat Gan | 153675 | 817 | 0.5316414511143648 | |
Ramat HaSharon | 45066 | 216 | 0.47929703102116894 | |
Ness Ziona | 48161 | 218 | 0.4526484084632795 | |
Herzliya | 93116 | 414 | 0.4446067270930882 | |
Kfar Saba | 98981 | 435 | 0.43947828371101527 | |
Beersheba | 205810 | 886 | 0.4304941450852728 |