From 8cf3b095822568f3130e1d55d9a22e8161460f3e Mon Sep 17 00:00:00 2001
From: "Joshua E. Jodesty" <joshua.jodesty@gmail.com>
Date: Thu, 3 Oct 2019 11:28:58 -0400
Subject: [PATCH] readme pt. 2: new build

---
 .gitignore                                    |   3 +-
 distroduce/README.md                          |  88 ++++++++++++++++++
 distroduce/action_policies.py                 |  30 +++++-
 distroduce/configuration/cluster.py           |  46 ---------
 .../configuration/launch_local_kafka.sh       |   4 +
 distroduce/dist/distroduce.zip                | Bin 20561 -> 31821 bytes
 distroduce/emr/launch.py                      |  39 ++++++++
 distroduce/local_messaging_sim.py             |  14 +--
 distroduce/messaging_sim.py                   |  10 +-
 distroduce/simulation.py                      |  77 +++++++++++++++
 distroduce/state_updates.py                   |  28 +++++-
 11 files changed, 276 insertions(+), 63 deletions(-)

diff --git a/.gitignore b/.gitignore
index c15c07f..40ae22d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -30,4 +30,5 @@ Simulation.md
 monkeytype.sqlite3
 
 distributed_produce/bash/
-distributed_produce/notes.txt
\ No newline at end of file
+distributed_produce/notes.txt
+notes.txt
\ No newline at end of file
diff --git a/distroduce/README.md b/distroduce/README.md
index e69de29..a057d01 100644
--- a/distroduce/README.md
+++ b/distroduce/README.md
@@ -0,0 +1,88 @@
+```
+   ___   _      __        _  __         __           __
+  / _ \ (_)___ / /_ ____ (_)/ /  __ __ / /_ ___  ___/ /
+ / // // /(_-</ __// __// // _ \/ // // __// -_)/ _  / 
+/____//_//___/\__//_/ _/_//_.__/\_,_/ \__/ \__/ \_,_/  
+  / _ \ ____ ___  ___/ /__ __ ____ ___                 
+ / ___// __// _ \/ _  // // // __// -_)                
+/_/   /_/   \___/\_,_/ \_,_/ \__/ \__/                 
+by Joshua E. Jodesty                                                       
+                                       
+```
+
+##Description:
+***Distributed Produce*** (**[distroduce](distroduce)**) is a message simulation and throughput benchmarking framework / 
+cadCAD execution mode that leverages Apache Spark and Kafka Producer for optimizing Kafka cluster configurations and 
+debugging real-time data transformations (i.e. Kafka Streams, Spark (Structured) Streaming). cadCAD's user-defined event 
+simulation framework is used to simulate messages sent to Kafka clusters.
+
+##Use Cases:
+* **Education:** I wanted to provide a tool for Insight Data Engineering Fellows implementing real-time data processing 
+that enables rapid and iterative design, debugging, and message publish benchmarking of Kafka clusters and real-time 
+data processing using Kafka Streams and Spark (Structured) Streaming.
+* **IoT:** Competes with *AWS IoT Device Simulator* and *Azure IoT Solution Acceleration: Device Simulation*. Unlike 
+these products, *Distributed Produce* enables a user-defined state updates and agent actions, as well as message publish 
+benchmarking
+
+##Get Started:
+
+### 0. Set Up Local Development Environment: see [Kafka Quickstart](https://kafka.apache.org/quickstart)
+**a.** Install `pyspark`
+```bash
+pip3 install pyspark
+``` 
+**b.** Install & Unzip Kafka, Create Kafka `test` topic, and Start Consumer
+```bash
+sh distroduce/configuration/launch_local_kafka.sh
+```
+**c.** Run Simulation locally
+```bash
+python3 distroduce/local_messaging_sim.py
+```
+
+### 1. Write Simulation: 
+* [Documentation](https://github.com/BlockScience/cadCAD/tree/master/documentation)
+* [Tutorials](https://github.com/BlockScience/cadCAD/tree/master/tutorials)
+
+**Note:** State Update and Policy Functions now have the additional / undocumented parameter `kafkaConfig`
+
+**a.** **Define Policy Functions:** Two users interacting on separate chat clients and entering / exiting chat rooms 
+* [Example](distroduce/action_policies.py)
+* [Documentation](https://github.com/BlockScience/cadCAD/tree/master/documentation#Policy-Functions)
+
+**b.** **Define State Update Functions:** Used for logging and maintaining state of user actions defined by policies
+* [Example](distroduce/state_updates.py)
+* [Documentation](https://github.com/BlockScience/cadCAD/tree/master/documentation#state-update-functions)
+
+**c.** **Define Initial Conditions & Partial State Update Block**
+* **Initial Conditions** - State Variables and their initial values
+    * [Example](distroduce/messaging_sim.py)
+    * [Documentation](https://github.com/BlockScience/cadCAD/tree/master/documentation#State-Variables)
+
+* **Partial State Update Block (PSUB)** - a set of State Update Functions and Policy Functions that update state records
+    * [Example](distroduce/simulation.py)
+    * [Documentation](https://github.com/BlockScience/cadCAD/tree/master/documentation#Partial-State-Update-Blocks)
+    ![](https://i.imgur.com/9rlX9TG.png)
+
+**d.** **Create Simulation Executor:** Used for running a simulation
+* [Local](distroduce/local_messaging_sim.py)
+* [EMR](distroduce/messaging_sim.py)
+
+### 2. [Configure EMR Cluster](distroduce/configuration/cluster.py)
+
+### 3. Launch EMR Cluster:
+```python
+from distroduce.emr.launch import launch_cluster
+from distroduce.configuration.cluster import ec2_attributes, bootstrap_actions, instance_groups, configurations
+region = 'us-east-1'
+cluster_name = 'distibuted_produce'
+launch_cluster(cluster_name, region, ec2_attributes, bootstrap_actions, instance_groups, configurations)
+```
+
+### 4. Execute Benchmark(s):
+* **Step 1:** ssh unto master node
+* **Step 2:** Spark Submit
+    ```
+    PRIVATE_IP=`hostname -I | xargs`
+    spark-submit --master yarn --py-files distroduce.zip messaging_sim.py $PRIVATE_IP
+    ```
diff --git a/distroduce/action_policies.py b/distroduce/action_policies.py
index 2c90c98..046f28a 100644
--- a/distroduce/action_policies.py
+++ b/distroduce/action_policies.py
@@ -1,7 +1,14 @@
 from datetime import datetime
 from kafka import KafkaProducer
 
-# Actions
+
+'''
+Function that produces a single actions taken by a user and its accompanying message.
+
+The results will be combined with a user-defined aggregation function (UDAF) 
+given to the `policy_ops` argument of `cadCAD.configuration.append_configs`.
+Current UDAF: `policy_ops=[lambda a, b: a + b]`
+'''
 def messages(client_id, room, action, _input, sender, receiver=None):
     return {
         'types': [action],
@@ -10,12 +17,15 @@ def messages(client_id, room, action, _input, sender, receiver=None):
                 'client': client_id, 'room': room, 'action': action,
                 'sender': sender, 'receiver': receiver,
                 'input': _input,
-                'creatred': datetime.now()
+                'created': datetime.now()
             }
         ]
     }
 
 
+'''
+Policy representing a user entering a chat room and its accompanying message
+'''
 def enter_action(state, room, user):
     def f(_g, step, sL, s, kafkaConfig):
         msgs = messages(state, room, 'enter', f"{user} enters {room}", user)
@@ -24,8 +34,16 @@ def enter_action(state, room, user):
         return msgs
     return f
 
-def message_actions(state, room, _input, sender, receiver):
-    msgs = messages(state, room, 'send', _input, sender, receiver)
+
+'''
+Policy representing a user sending a message to a receiver within a chat room
+and its accompanying message
+
+A Kafka Producer is used to send messages to a Kafka cluster. 
+The configuration of the Kafka Producer via `cadCAD.engine.ExecutionContext`
+'''
+def message_actions(state, room, message_input, sender, receiver):
+    msgs = messages(state, room, 'send', message_input, sender, receiver)
     msgs_list = msgs['messages']
     def send_action(_g, step, sL, s, kafkaConfig):
         start_time = datetime.now()
@@ -40,6 +58,10 @@ def message_actions(state, room, _input, sender, receiver):
 
     return send_action
 
+
+'''
+Policy representing a user exiting a chat room and its accompanying message
+'''
 def exit_action(state, room, user):
     def f(_g, step, sL, s, kafkaConfig):
         msgs = messages(state, room, 'exit', f"{user} exited {room}", user)
diff --git a/distroduce/configuration/cluster.py b/distroduce/configuration/cluster.py
index 7a8371c..390908e 100644
--- a/distroduce/configuration/cluster.py
+++ b/distroduce/configuration/cluster.py
@@ -1,6 +1,3 @@
-import os, json, boto3
-from typing import List
-
 ec2_attributes = {
     "KeyName":"joshua-IAM-keypair",
     "InstanceProfile":"EMR_EC2_DefaultRole",
@@ -80,46 +77,3 @@ configurations = [
         }
     }
 ]
-
-
-
-def create_distroduce_cluster(name, region, ec2_attributes, bootstrap_actions, instance_groups, configurations):
-    def log_uri(name, region):
-        return f's3n://{name}-{region}/elasticmapreduce/'
-
-    os.system(f"""
-        aws emr create-cluster \
-        --applications Name=Hadoop Name=Hive Name=Spark \
-        --ec2-attributes '{json.dumps(ec2_attributes)}' \
-        --release-label emr-5.26.0 \
-        --log-uri '{str(log_uri(name, region))}' \
-        --instance-groups '{json.dumps(instance_groups)}' \
-        --configurations '{json.dumps(configurations)}' \
-        --auto-scaling-role EMR_AutoScaling_DefaultRole \
-        --bootstrap-actions '{json.dumps(bootstrap_actions)}' \
-        --ebs-root-volume-size 10 \
-        --service-role EMR_DefaultRole \
-        --enable-debugging \
-        --name '{name}' \
-        --scale-down-behavior TERMINATE_AT_TASK_COMPLETION \
-        --region {region}
-    """)
-
-
-def benchmark(names: List[str], region, ec2_attributes, bootstrap_actions, instance_groups, configurations):
-    current_dir = os.path.dirname(__file__)
-    s3 = boto3.client('s3')
-    bucket = 'insightde'
-
-    file = 'distroduce.sh'
-    abs_path = os.path.join(current_dir, file)
-    key = f'emr/bootstraps/{file}'
-
-    s3.upload_file(abs_path, bucket, key)
-    for name in names:
-        create_distroduce_cluster(name, region, ec2_attributes, bootstrap_actions, instance_groups, configurations)
-
-
-name = 'distibuted_produce'
-region = 'us-east-1'
-benchmark([name], region, ec2_attributes, bootstrap_actions, instance_groups, configurations)
\ No newline at end of file
diff --git a/distroduce/configuration/launch_local_kafka.sh b/distroduce/configuration/launch_local_kafka.sh
index 497e88f..87624bd 100644
--- a/distroduce/configuration/launch_local_kafka.sh
+++ b/distroduce/configuration/launch_local_kafka.sh
@@ -1,4 +1,8 @@
 #!/bin/bash
+wget http://apache.spinellicreations.com/kafka/2.3.0/kafka_2.12-2.3.0.tgz
+tar -xzf kafka_2.12-2.3.0.tgz
+cd kafka_2.12-2.3.0
 bin/zookeeper-server-start.sh config/zookeeper.properties &
 bin/kafka-server-start.sh config/server.properties &
 bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 1 --partitions 1 --topic test
+bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic test --from-beginning
diff --git a/distroduce/dist/distroduce.zip b/distroduce/dist/distroduce.zip
index 866365d6c1c6ea658352684d3ebc749ffe09f211..d571a211732305367ade96bd37eb07c0e99543ec 100644
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diff --git a/distroduce/emr/launch.py b/distroduce/emr/launch.py
index e69de29..8257b54 100644
--- a/distroduce/emr/launch.py
+++ b/distroduce/emr/launch.py
@@ -0,0 +1,39 @@
+import os, json, boto3
+from typing import List
+
+
+def launch_cluster(name, region, ec2_attributes, bootstrap_actions, instance_groups, configurations):
+    def log_uri(name, region):
+        return f's3n://{name}-{region}/elasticmapreduce/'
+
+    os.system(f"""
+        aws emr create-cluster \
+        --applications Name=Hadoop Name=Hive Name=Spark \
+        --ec2-attributes '{json.dumps(ec2_attributes)}' \
+        --release-label emr-5.26.0 \
+        --log-uri '{str(log_uri(name, region))}' \
+        --instance-groups '{json.dumps(instance_groups)}' \
+        --configurations '{json.dumps(configurations)}' \
+        --auto-scaling-role EMR_AutoScaling_DefaultRole \
+        --bootstrap-actions '{json.dumps(bootstrap_actions)}' \
+        --ebs-root-volume-size 10 \
+        --service-role EMR_DefaultRole \
+        --enable-debugging \
+        --name '{name}' \
+        --scale-down-behavior TERMINATE_AT_TASK_COMPLETION \
+        --region {region}
+    """)
+
+
+# def benchmark(names: List[str], region, ec2_attributes, bootstrap_actions, instance_groups, configurations):
+#     current_dir = os.path.dirname(__file__)
+#     s3 = boto3.client('s3')
+#     bucket = 'insightde'
+#
+#     file = 'distroduce.sh'
+#     abs_path = os.path.join(current_dir, file)
+#     key = f'emr/bootstraps/{file}'
+#
+#     s3.upload_file(abs_path, bucket, key)
+#     for name in names:
+#         launch_cluster(name, region, ec2_attributes, bootstrap_actions, instance_groups, configurations)
\ No newline at end of file
diff --git a/distroduce/local_messaging_sim.py b/distroduce/local_messaging_sim.py
index de7bd59..5c29896 100644
--- a/distroduce/local_messaging_sim.py
+++ b/distroduce/local_messaging_sim.py
@@ -9,7 +9,8 @@ from distroduce.spark.session import sc
 from distroduce.executor.spark import distributed_produce
 
 if __name__ == "__main__":
-    intitial_conditions = {
+    # Initial States
+    initial_conditions = {
         'record_creation': datetime.now(),
         'client_a': {'users': [], 'messages': [], 'msg_count': 0, 'send_time': 0.0},
         'client_b': {'users': [], 'messages': [], 'msg_count': 0, 'send_time': 0.0},
@@ -17,20 +18,21 @@ if __name__ == "__main__":
         'total_send_time': 0.000000
     }
 
-    # N = 5 = 10000 / (500 x 4)
-    # T = 500
+    '''
+    Simulation Configuration:
+    N = Simulation Runs
+    T = Timesteps for each Partial State Update Block
+    '''
     sim_config = config_sim(
         {
             "N": 1,
             "T": range(10),
-            # "T": range(5000),
         }
     )
 
     exec_mode = ExecutionMode()
     kafkaConfig = {'send_topic': 'test', 'producer_config': {'bootstrap_servers': f'localhost:9092', 'acks': 'all'}}
-    # kafkaConfig = {'send_topic': 'test', 'producer_config': {'bootstrap_servers': f'{sys.argv[1]}:9092', 'acks': 'all'}}
     dist_proc_ctx = ExecutionContext(context=exec_mode.dist_proc, method=distributed_produce, kafka_config=kafkaConfig)
     run = Executor(exec_context=dist_proc_ctx, configs=configs, spark_context=sc)
 
-    main(run, sim_config, intitial_conditions, sim_composition)
+    main(run, sim_config, initial_conditions, sim_composition)
diff --git a/distroduce/messaging_sim.py b/distroduce/messaging_sim.py
index 5d80ca7..3a90dfa 100644
--- a/distroduce/messaging_sim.py
+++ b/distroduce/messaging_sim.py
@@ -9,7 +9,8 @@ from distroduce.spark.session import sc
 from distroduce.executor.spark import distributed_produce
 
 if __name__ == "__main__":
-    intitial_conditions = {
+    # Initial States
+    initial_conditions = {
         'record_creation': datetime.now(),
         'client_a': {'users': [], 'messages': [], 'msg_count': 0, 'send_time': 0.0},
         'client_b': {'users': [], 'messages': [], 'msg_count': 0, 'send_time': 0.0},
@@ -17,6 +18,11 @@ if __name__ == "__main__":
         'total_send_time': 0.000000
     }
 
+    '''
+    Simulation Configuration:
+    N = Simulation Runs
+    T = Timesteps for each Partial State Update Block
+    '''
     sim_config = config_sim(
         {
             "N": 1,
@@ -29,4 +35,4 @@ if __name__ == "__main__":
     dist_proc_ctx = ExecutionContext(context=exec_mode.dist_proc, method=distributed_produce, kafka_config=kafkaConfig)
     run = Executor(exec_context=dist_proc_ctx, configs=configs, spark_context=sc)
 
-    main(run, sim_config, intitial_conditions, sim_composition)
+    main(run, sim_config, initial_conditions, sim_composition)
diff --git a/distroduce/simulation.py b/distroduce/simulation.py
index e69de29..6bd3695 100644
--- a/distroduce/simulation.py
+++ b/distroduce/simulation.py
@@ -0,0 +1,77 @@
+import sys
+from pprint import pprint
+
+import pandas as pd
+from tabulate import tabulate
+
+from cadCAD.utils import arrange_cols
+from cadCAD.configuration import append_configs
+
+from distroduce.action_policies import enter_action, message_actions, exit_action
+from distroduce.state_updates import send_message, count_messages, add_send_time, current_time
+
+# State Updates
+variables = {
+    'client_a': send_message('client_a'),
+    'client_b': send_message('client_b'),
+    'total_msg_count': count_messages,
+    'total_send_time': add_send_time,
+    'record_creation': current_time('record_creation')
+}
+
+# Action Policies
+policy_group_1 = {
+    "action_1": enter_action('server', 'room_1', 'A'),
+    "action_2": enter_action('server', 'room_1', 'B')
+}
+
+policy_group_2 = {
+    "action_1": message_actions('client_A', 'room_1', "Hi B", 'A', 'B'),
+    "action_2": message_actions('client_B', 'room_1', "Hi A", 'B', 'A')
+}
+
+policy_group_3 = {
+    "action_1": message_actions('client_A', 'room_1', "Bye B", 'A', 'B'),
+    "action_2": message_actions('client_B', 'room_1', "Bye A", 'B', 'A')
+}
+
+policy_group_4 = {
+    "action_1": exit_action('server', 'room_1', 'A'),
+    "action_2": exit_action('server', 'room_1', 'B')
+}
+
+policy_groups = [policy_group_1, policy_group_2, policy_group_3, policy_group_4]
+# Partial State update Block
+sim_composition = [{'policies': policy_group, 'variables': variables} for policy_group in policy_groups]
+
+
+def main(executor, sim_config, intitial_conditions, sim_composition):
+    append_configs(
+        user_id='Joshua',
+        sim_configs=sim_config,
+        initial_state=intitial_conditions,
+        partial_state_update_blocks=sim_composition,
+        policy_ops=[lambda a, b: a + b]
+    )
+    pprint(sim_composition)
+
+    i = 0
+    for raw_result, tensor_field in executor.execute():
+        result = arrange_cols(pd.DataFrame(raw_result), False)[
+            [
+                'run_id', 'timestep', 'substep',
+                'record_creation', 'total_msg_count', 'total_send_time'
+            ]
+        ]
+        print()
+        if i == 0:
+            print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
+        last = result.tail(1)
+        last['msg_per_sec'] = last['total_msg_count'] / last['total_send_time']
+        print("Output: Head")
+        print(tabulate(result.head(5), headers='keys', tablefmt='psql'))
+        print("Output: Tail")
+        print(tabulate(result.tail(5), headers='keys', tablefmt='psql'))
+        print(tabulate(last, headers='keys', tablefmt='psql'))
+        print()
+        i += 1
diff --git a/distroduce/state_updates.py b/distroduce/state_updates.py
index 0e71932..3022b21 100644
--- a/distroduce/state_updates.py
+++ b/distroduce/state_updates.py
@@ -2,7 +2,12 @@ from copy import deepcopy
 from datetime import datetime
 from functools import reduce
 
-# State Updates
+add = lambda a, b: a + b
+
+
+'''
+Function that maintains the state of users in a chat room
+'''
 def update_users(users, actions, action_types=['send','enter','exit']):
     users = deepcopy(users)
     for action_type in action_types:
@@ -18,13 +23,17 @@ def update_users(users, actions, action_types=['send','enter','exit']):
                         users.remove(user) # remove_exited
     return users
 
-add = lambda a, b: a + b
+
+'''
+State Update used to counts sent messages
+'''
 def count_messages(_g, step, sL, s, actions, kafkaConfig):
     return 'total_msg_count', s['total_msg_count'] + reduce(add, actions['msg_counts'])
 
-def add_send_time(_g, step, sL, s, actions, kafkaConfig):
-    return 'total_send_time', s['total_send_time'] + reduce(add, actions['send_times'])
 
+'''
+State Update used to create to log message events
+'''
 def send_message(state):
     return lambda _g, step, sL, s, actions, kafkaConfig: (
         state,
@@ -36,5 +45,16 @@ def send_message(state):
         }
     )
 
+
+'''
+State Update used to sum the time taken for the Kafka Producer to send messages between users
+'''
+def add_send_time(_g, step, sL, s, actions, kafkaConfig):
+    return 'total_send_time', s['total_send_time'] + reduce(add, actions['send_times'])
+
+
+'''
+State Update used to record the event record creation time
+'''
 def current_time(state):
     return lambda _g, step, sL, s, actions, kafkaConfig: (state, datetime.now())
\ No newline at end of file