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Merge pull request #11 from radibnia77/main
Add script to get pipeline statistics
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# Licensed to the Apache Software Foundation (ASF) under one | ||
# or more contributor license agreements. See the NOTICE file | ||
# distributed with this work for additional information | ||
# regarding copyright ownership. The ASF licenses this file | ||
# to you 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. | ||
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from airflow import DAG | ||
import datetime as dt | ||
from airflow.contrib.operators.spark_submit_operator import SparkSubmitOperator | ||
from datetime import timedelta | ||
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default_args = { | ||
'owner': 'lookalike_application', | ||
'depends_on_past': False, | ||
'start_date': dt.datetime(2021, 7, 28), | ||
'retries': 1, | ||
'retry_delay': timedelta(minutes=5), | ||
} | ||
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dag = DAG( | ||
'lookalike_application', | ||
default_args=default_args, | ||
schedule_interval=None, | ||
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) | ||
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def sparkOperator( | ||
file, | ||
task_id, | ||
**kwargs | ||
): | ||
return SparkSubmitOperator( | ||
application='/home/airflow/airflow-apps/lookalike-model/lookalike_model/application/pipeline/{}'.format(file), | ||
application_args=['/home/airflow/airflow-apps/lookalike-model/lookalike_model/application/pipeline/config.yml'], | ||
conn_id='spark_default', | ||
executor_memory='8G', | ||
conf={'spark.driver.maxResultSize': '5g', 'spark.hadoop.hive.exec.dynamic.partition': True, 'spark.hadoop.hive.exec.dynamic.partition.mode': 'nonstrict'}, | ||
driver_memory='8G', | ||
executor_cores=5, | ||
num_executors=20, | ||
task_id=task_id, | ||
dag=dag, | ||
**kwargs | ||
) | ||
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score_generator = sparkOperator('score_generator.py', 'lookalike_score_generator') | ||
score_vector_table = sparkOperator('score_vector_table.py', 'lookalike_score_vector_table') | ||
score_vector_rebucketing = sparkOperator('score_vector_rebucketing.py', 'lookalike_score_vector_rebucketing') | ||
top_n_similarity_table_generator = sparkOperator('top_n_similarity_table_generator.py', 'lookalike_top_n_similarity_table_generator') | ||
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score_generator >> score_vector_table >> score_vector_rebucketing >> top_n_similarity_table_generator |
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Model/lookalike-model/doc/ssd-v2.pdf
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product_tag: 'lookalike' | ||
pipeline_tag: '08042021' | ||
score_generator: | ||
input: | ||
log_table : "lookalike_03042021_logs" | ||
did_table: "lookalike_03042021_trainready" | ||
keywords_table: "din_ad_keywords_09172020" | ||
test_table: "lookalike_trainready_jimmy_test" | ||
din_model_tf_serving_url: "http://10.193.217.105:8506/v1/models/lookalike3:predict" | ||
din_model_tf_serving_url: "http://10.193.217.105:8506/v1/models/lookalike:predict" | ||
din_model_length: 20 | ||
seeduser_table : "lookalike_seeduser" | ||
number_of_seeduser: 1000 | ||
extend: 2000 | ||
alg: "euclidean" ##### currently just support "euclideand" and "dot" | ||
output: | ||
did_score_table: "lookalike_score_01112021" | ||
score_norm_table: "lookalike_score_norm_01112021" | ||
did_score_table: "{product_tag}_score_{pipeline_tag}" | ||
score_norm_table: "{product_tag}_score_norm_{pipeline_tag}" | ||
normalize: False | ||
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score_vector: | ||
keywords_table: "din_ad_keywords_09172020" | ||
score_norm_table: "lookalike_score_norm_01112021" | ||
score_vector_table: "lookalike_score_vector_01112021" | ||
score_norm_table: "{product_tag}_score_norm_{pipeline_tag}" | ||
score_vector_table: "{product_tag}_score_vector_{pipeline_tag}" | ||
did_bucket_size: 2 | ||
did_bucket_step: 2 | ||
score_vector_rebucketing: | ||
did_bucket_size: 2 | ||
did_bucket_step: 2 | ||
alpha_did_bucket_size: 1000 | ||
score_vector_alpha_table: 'lookalike_score_vector_alpha_01112021' | ||
alpha_did_bucket_size: 20 #default=1000 | ||
score_vector_alpha_table: '{product_tag}_score_vector_alpha_{pipeline_tag}' | ||
top_n_similarity: | ||
alpha_did_bucket_step: 100 | ||
top_n: 100 | ||
similarity_table: "lookalike_similarity_01112021" | ||
did_bucket_step: 1 | ||
alpha_did_bucket_step: 10 | ||
top_n: 10 | ||
similarity_table: "{product_tag}_similarity_{pipeline_tag}" |
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#!/bin/bash | ||
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spark-submit --executor-memory 16G --driver-memory 24G --num-executors 16 --executor-cores 5 --master yarn --conf spark.driver.maxResultSize=8g seed_user_selector.py config.yml "29" | ||
# Not used as part of pipeline | ||
spark-submit --master yarn --num-executors 20 --executor-cores 5 --executor-memory 8G --driver-memory 8G --conf spark.driver.maxResultSize=5g --conf spark.hadoop.hive.exec.dynamic.partition=true --conf spark.hadoop.hive.exec.dynamic.partition.mode=nonstrict seed_user_selector.py config.yml "29" | ||
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spark-submit --executor-memory 16G --driver-memory 24G --num-executors 16 --executor-cores 5 --master yarn --conf spark.driver.maxResultSize=8g score_generator.py config.yml | ||
spark-submit --master yarn --num-executors 20 --executor-cores 5 --executor-memory 8G --driver-memory 8G --conf spark.driver.maxResultSize=5g --conf spark.hadoop.hive.exec.dynamic.partition=true --conf spark.hadoop.hive.exec.dynamic.partition.mode=nonstrict score_generator.py config.yml | ||
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spark-submit --master yarn --num-executors 20 --executor-cores 5 --executor-memory 8G --driver-memory 8G --conf spark.driver.maxResultSize=5g --conf spark.hadoop.hive.exec.dynamic.partition=true --conf spark.hadoop.hive.exec.dynamic.partition.mode=nonstrict score_vector_table.py config.yml | ||
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spark-submit --master yarn --num-executors 20 --executor-cores 5 --executor-memory 8G --driver-memory 8G --conf spark.driver.maxResultSize=5g --conf spark.hadoop.hive.exec.dynamic.partition=true --conf spark.hadoop.hive.exec.dynamic.partition.mode=nonstrict score_vector_rebucketing.py config. | ||
spark-submit --master yarn --num-executors 20 --executor-cores 5 --executor-memory 8G --driver-memory 8G --conf spark.driver.maxResultSize=5g --conf spark.hadoop.hive.exec.dynamic.partition=true --conf spark.hadoop.hive.exec.dynamic.partition.mode=nonstrict score_vector_rebucketing.py config.yml | ||
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spark-submit --master yarn --num-executors 20 --executor-cores 5 --executor-memory 16G --driver-memory 16G --conf spark.driver.maxResultSize=5g --conf spark.hadoop.hive.exec.dynamic.partition=true --conf spark.hadoop.hive.exec.dynamic.partition.mode=nonstrict top_n_similarity_table_generator.py config.yml | ||
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spark-submit --executor-memory 16G --driver-memory 24G --num-executors 16 --executor-cores 5 --master yarn --conf spark.driver.maxResultSize=8g validation.py config.yml "29" | ||
# Not used as part of pipeline | ||
spark-submit ---master yarn --num-executors 20 --executor-cores 5 --executor-memory 8G --driver-memory 8G --conf spark.driver.maxResultSize=5g --conf spark.hadoop.hive.exec.dynamic.partition=true --conf spark.hadoop.hive.exec.dynamic.partition.mode=nonstrict validation.py config.yml "29" | ||
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