Refactor

.vscode/settings.json

@@ -1,7 +1,10 @@
 {
-    "python.linting.pylintEnabled": false,
+    // "python.linting.pylintEnabled": false,
     "search.exclude": {
         "build/**": true,
         "bin/**": true
-    }
+    },
+    "python.autoComplete.extraPaths": [
+        "${workspaceRoot}/node"
+    ]
 }

dtde/clusterlib.py

@@ -1,9 +1,7 @@
-from . import util, constants, azure_api, upload_node_scripts
-import random
 from datetime import datetime, timedelta
-import azure.batch.models as batch_models
 from subprocess import call
-import sys
+import azure.batch.models as batch_models
+from . import util, constants, azure_api, upload_node_scripts
 
 pool_admin_user = batch_models.UserIdentity(
     auto_user=batch_models.AutoUserSpecification(
@@ -24,9 +22,9 @@ def cluster_install_cmd(zip_resource_file: batch_models.ResourceFile, custom_scr
         # To avoid error: "sudo: sorry, you must have a tty to run sudo"
         'sed -i -e "s/Defaults    requiretty.*/ #Defaults    requiretty/g" /etc/sudoers',
         '/bin/sh -c "unzip $AZ_BATCH_TASK_WORKING_DIR/%s"' % zip_resource_file.file_path,
-        'chmod 777 $AZ_BATCH_TASK_WORKING_DIR/setup_node.sh',
-        'dos2unix $AZ_BATCH_TASK_WORKING_DIR/setup_node.sh', # Convert windows line ending to unix if applicable
-        '/bin/bash -c "$AZ_BATCH_TASK_WORKING_DIR/setup_node.sh"'
+        'chmod 777 $AZ_BATCH_TASK_WORKING_DIR/main.sh',
+        'dos2unix $AZ_BATCH_TASK_WORKING_DIR/main.sh', # Convert windows line ending to unix if applicable
+        '/bin/bash -c "$AZ_BATCH_TASK_WORKING_DIR/main.sh"'
     ]
 
     if custom_script_file is not None:
@@ -119,7 +117,7 @@ def cluster_start_cmd(webui_port, jupyter_port):
     ]
 
 
-def generate_cluster_start_task(zip_resource_file: batch_models.ResourceFile, custom_script: str = None):
+def generate_cluster_start_task(cluster_id: str, zip_resource_file: batch_models.ResourceFile, custom_script: str = None):
     """
         This will return the start task object for the pool to be created.
         :param custom_script str: Path to a local file to be uploaded to storage and run after spark started.
@@ -131,7 +129,7 @@ def generate_cluster_start_task(zip_resource_file: batch_models.ResourceFile, cu
     if custom_script is not None:
         resource_files.append(
             util.upload_file_to_container(
-                container_name=pool_id,
+                container_name=cluster_id,
                 file_path=custom_script,
                 use_full_path=True))
 
@@ -196,7 +194,7 @@ def create_cluster(
         vm_size=vm_size,
         target_dedicated_nodes=vm_count,
         target_low_priority_nodes=vm_low_pri_count,
-        start_task=generate_cluster_start_task(zip_resource_file, custom_script),
+        start_task=generate_cluster_start_task(pool_id, zip_resource_file, custom_script),
         enable_inter_node_communication=True,
         max_tasks_per_node=1)
 

dtde/upload_node_scripts.py

@@ -1,39 +1,45 @@
 import os
 import zipfile
-from . import constants, util
+from . import util
 
 root = os.path.join(os.path.dirname(os.path.realpath(__file__)), "..")
 
-local_tmp_zipfile = "tmp/node-scripts.zip";
+local_tmp_zipfile = "tmp/node-scripts.zip"
+
 
 def ensure_dir(file_path):
     directory = os.path.dirname(file_path)
     if not os.path.exists(directory):
         os.makedirs(directory)
 
+
 def zipdir(path, ziph):
     """
         Zip all the files in the given directory into the zip file handler
     """
-    for root, dirs, files in os.walk(path):
+    for base, _, files in os.walk(path):
+        relative_folder = os.path.relpath(base, path)
         for file in files:
-            ziph.write(os.path.join(root, file), file)
+            ziph.write(os.path.join(base, file),
+                       os.path.join(relative_folder, file))
 
 
-def zip():
+def create_zip():
     ensure_dir(local_tmp_zipfile)
     zipf = zipfile.ZipFile(local_tmp_zipfile, 'w', zipfile.ZIP_DEFLATED)
-    zipdir(os.path.join(root, "node"), zipf)
+    zipdir(os.path.join(root, "node_scripts"), zipf)
     zipf.close()
     print("Ziped file")
 
+
 def upload():
     print("Uploading node scripts...")
     return util.upload_file_to_container(
-                container_name = "spark-node-scripts", 
-                file_path = local_tmp_zipfile, 
-                use_full_path = False)
+        container_name="spark-node-scripts",
+        file_path=local_tmp_zipfile,
+        use_full_path=False)
+
 
 def zip_and_upload():
-    zip()
+    create_zip()
     return upload()

node/clear_metadata.py

@@ -1,30 +0,0 @@
-import os
-import azure.batch.batch_service_client as batch
-import azure.batch.batch_auth as batchauth
-import azure.batch.models as batchmodels
-
-pool_id = "sparktest"
-node_id = "abc"
-
-master_node_metadata_key = "_spark_master_node"
-
-def get_client():
-    # account_name = os.environ["AZ_BATCH_ACCOUNT_NAME"]
-    # account_key = os.environ["ACCOUNT_KEY"]
-    # account_url = os.environ["ACCOUNT_URL"]
-
-    account_name = "prodtest1"
-    account_key =  "o7qjfiRHz1CrjeDLIRUGTZfepWkdJUTc1OHcNEuD4QKUdWFzJ2rAXZlLv9MCyL8ZPXsBTSxash3q+sLdQLEJXA=="
-    account_url =  "https://prodtest1.brazilsouth.batch.azure.com"
-
-    credentials = batchauth.SharedKeyCredentials(
-        account_name,
-        account_key)
-    return batch.BatchServiceClient(credentials, base_url=account_url)
-
-if __name__ == "__main__":
-    client = get_client()
-    client.pool.patch(pool_id, batchmodels.PoolPatchParameter(
-        metadata=[],
-    ))
-    print("Cleared metadata!")

node_scripts/core/config.py

@@ -0,0 +1,25 @@
+import os
+import azure.batch.batch_service_client as batch
+import azure.batch.batch_auth as batchauth
+
+account_name = os.environ["AZ_BATCH_ACCOUNT_NAME"]
+account_key = os.environ["ACCOUNT_KEY"]
+account_url = os.environ["ACCOUNT_URL"]
+pool_id = os.environ["AZ_BATCH_POOL_ID"]
+node_id = os.environ["AZ_BATCH_NODE_ID"]
+is_dedicated = os.environ["AZ_BATCH_NODE_IS_DEDICATED"]
+
+
+def get_client() -> batch.BatchServiceClient:
+    credentials = batchauth.SharedKeyCredentials(
+        account_name,
+        account_key)
+    return batch.BatchServiceClient(credentials, base_url=account_url)
+
+
+batch_client = get_client()
+
+print("Pool id is", node_id)
+print("Node id is", node_id)
+print("Account name", account_name)
+print("Is dedicated", is_dedicated)

node_scripts/install/pick_master.py

@@ -2,34 +2,18 @@
     This is the code that all nodes will run in their start task to try to allocate the master
 """
 
-import os
 import azure.batch.batch_service_client as batch
 import azure.batch.batch_auth as batchauth
 import azure.batch.models as batchmodels
 import azure.batch.models.batch_error as batcherror
+from core import config
 
-pool_id = os.environ["AZ_BATCH_POOL_ID"]
-node_id = os.environ["AZ_BATCH_NODE_ID"]
-account_name = os.environ["AZ_BATCH_ACCOUNT_NAME"]
-account_key = os.environ["ACCOUNT_KEY"]
-account_url = os.environ["ACCOUNT_URL"]
-is_dedicated = os.environ["AZ_BATCH_NODE_IS_DEDICATED"]
-
-
-print("Pool id is", node_id)
-print("Node id is", node_id)
-print("Account name", account_name)
-print("Is dedicated", is_dedicated)
 
 master_node_metadata_key = "_spark_master_node"
 
 
-def get_client():
-
-    credentials = batchauth.SharedKeyCredentials(
-        account_name,
-        account_key)
-    return batch.BatchServiceClient(credentials, base_url=account_url)
+class CannotAllocateMasterError(Exception):
+    pass
 
 
 def get_master_node_id(pool: batchmodels.CloudPool):
@@ -49,10 +33,10 @@ def get_master_node_id(pool: batchmodels.CloudPool):
 def try_assign_self_as_master(client: batch.BatchServiceClient, pool: batchmodels.CloudPool):
     currentMetadata = pool.metadata or []
     newMetadata = currentMetadata + \
-        [{"name": master_node_metadata_key, "value": node_id}]
+        [{"name": master_node_metadata_key, "value": config.node_id}]
 
     try:
-        client.pool.patch(pool_id, batchmodels.PoolPatchParameter(
+        client.pool.patch(config.pool_id, batchmodels.PoolPatchParameter(
             metadata=newMetadata
         ), batchmodels.PoolPatchOptions(
             if_match=pool.e_tag,
@@ -63,12 +47,16 @@ def try_assign_self_as_master(client: batch.BatchServiceClient, pool: batchmodel
         return False
 
 
-def find_master(client: batch.BatchServiceClient):
+def find_master(client: batch.BatchServiceClient) -> bool:
+    """
+        Try to set a master for the cluster. If the node is dedicated it will try to assign itself if none already claimed it.
+        :returns bool: If the node is the master it returns true otherwise returns false
+    """
     # If not dedicated the node cannot be a master
-    if not is_dedicated:
-        return True
+    if not config.is_dedicated:
+        return False
     for i in range(0, 5):
-        pool = client.pool.get(pool_id)
+        pool = client.pool.get(config.pool_id)
         master = get_master_node_id(pool)
 
         if master:
@@ -79,20 +67,7 @@ def find_master(client: batch.BatchServiceClient):
             result = try_assign_self_as_master(client, pool)
 
             if result:
-                print("The battle has been won! Node %s is the new master.", node_id)
+                print("The battle has been won! Node %s is the new master.", config.node_id)
                 return True
 
-    print("Unable to assign node as a master in 5 tries")
-    return False
-
-
-def run():
-    client = get_client()
-    result = find_master(client)
-
-    if not result:
-        exit(1)
-
-
-if __name__ == "__main__":
-    run()
+    raise CannotAllocateMasterError("Unable to assign node as a master in 5 tries")

node_scripts/install/spark.py

@@ -0,0 +1,116 @@
+"""
+    Code that handle spark configuration
+"""
+import time
+import azure.batch.batch_service_client as batch
+import azure.batch.models as batchmodels
+from core import config
+
+batch_client = config.batch_client
+
+
+def get_pool() -> batchmodels.CloudPool:
+    return batch_client.pool.get(config.pool_id)
+
+
+def list_nodes() -> List[batchmodels.ComputeNode]:
+    return batch_client.compute_node.list(config.pool_id)
+
+
+def wait_for_pool_ready() -> batchmodels.CloudPool:
+    while True:
+        pool = get_pool()
+        if pool.state == batchmodels.AllocationState.steady
+            return pool
+        else:
+            print("Waiting for pool to be steady.")
+            time.sleep(5)  # Sleep for 10 seconds before trying again
+
+
+def connect_node(batch_client: batch.BatchServiceClient):
+    pool = wait_for_pool_ready()
+    print("Pool is now steady. Setting up master")
+
+    spark_home = "/dsvm/tools/spark/current"
+    spark_conf_folder = os.path.join(spark_home, "conf")
+
+    nodes = list_nodes()
+
+    for node in nodes:
+        
+    return [
+        # set SPARK_HOME environment vars
+        'export PATH=$PATH:$SPARK_HOME/bin',
+
+        # copy a 'slaves' file from the slaves.template in $SPARK_HOME/conf
+        'cp $SPARK_HOME/conf/slaves.template $SPARK_HOME/conf/slaves'
+
+        # delete existing content & create a new line in the slaves file
+        'echo > $SPARK_HOME/conf/slaves',
+
+        # make empty 'master' file in $SPARK/conf
+        'cp $SPARK_HOME/conf/slaves $SPARK_HOME/conf/master',
+
+        # add batch pool ips to newly created slaves files
+        'IFS="," read -r -a workerips <<< $AZ_BATCH_HOST_LIST',
+        'for index in "${!workerips[@]}"',
+        'do echo "${workerips[index]}"',
+        'if [ "${AZ_BATCH_MASTER_NODE%:*}" = "${workerips[index]}" ]',
+        'then echo "${workerips[index]}" >> $SPARK_HOME/conf/master',
+        'else echo "${workerips[index]}" >> $SPARK_HOME/conf/slaves',
+        'fi',
+        'done'
+    ]
+
+
+def start_cmd(webui_port, jupyter_port):
+    return [
+        # set SPARK_HOME environment vars
+        'export SPARK_HOME=/dsvm/tools/spark/current',
+        'export PATH=$PATH:$SPARK_HOME/bin',
+
+        # get master node ip
+        'export MASTER_NODE=$(cat $SPARK_HOME/conf/master)',
+
+        # kick off start-all spark command (which starts web ui)
+        '($SPARK_HOME/sbin/start-all.sh --webui-port ' + str(webui_port) + ' &)',
+
+        # jupyter setup: remove auth
+        '/anaconda/envs/py35/bin/jupyter notebook --generate-config',
+        'echo >> $HOME/.jupyter/jupyter_notebook_config.py',
+        'echo c.NotebookApp.token=\\\"\\\" >> $HOME/.jupyter/jupyter_notebook_config.py',
+        'echo c.NotebookApp.password=\\\"\\\" >> $HOME/.jupyter/jupyter_notebook_config.py',
+
+        # create jupyter kernal for pyspark
+        'rm -rf /usr/local/share/jupyter/kernels/*',
+        'mkdir /usr/local/share/jupyter/kernels/pyspark',
+        'touch /usr/local/share/jupyter/kernels/pyspark/kernel.json',
+        'echo { ' +
+        '\\\"display_name\\\": \\\"PySpark\\\", ' +
+        '\\\"language\\\": \\\"python\\\", ' +
+        '\\\"argv\\\": [ ' +
+        '\\\"/usr/bin/python3\\\", ' +
+        '\\\"-m\\\", ' +
+        '\\\"ipykernel\\\", ' +
+        '\\\"-f\\\", ' +
+        '\\\"{connection_file}\\\" ' +
+        '], ' +
+        '\\\"env\\\": { ' +
+        '\\\"SPARK_HOME\\\": \\\"/dsvm/tools/spark/current\\\", ' +
+        '\\\"PYSPARK_PYTHON\\\": \\\"/usr/bin/python3\\\", ' +
+        '\\\"PYSPARK_SUBMIT_ARGS\\\": ' +
+        '\\\"--master spark://${MASTER_NODE%:*}:7077 ' +
+        # '--executor-memory 6400M ' +
+        # '--driver-memory 6400M ' +
+        'pyspark-shell\\\" ' +
+        '}' +
+        '} >> /usr/local/share/jupyter/kernels/pyspark/kernel.json',
+
+        # start jupyter notebook
+        '(PYSPARK_DRIVER_PYTHON=/anaconda/envs/py35/bin/jupyter ' +
+        'PYSPARK_DRIVER_PYTHON_OPTS="notebook --no-browser --port=' + str(jupyter_port) + '" ' +
+        'pyspark &)'  # +
+        #     '--master spark://${MASTER_NODE%:*}:7077 '  +
+        #     '--executor-memory 6400M ' +
+        #     '--driver-memory 6400M &)'
+    ]

node_scripts/main.py

@@ -0,0 +1,37 @@
+import sys
+from install import pick_master
+from core import config
+
+
+def setup_as_master():
+    print("Setting up as master.")
+
+
+def setup_as_worker():
+    print("Setting up as worker.")
+
+
+def run():
+
+    if len(sys.argv) < 2:
+        print("Error: Expected at least one argument")
+        exit(1)
+
+    action = sys.argv[1]
+
+    if action == "install":
+
+        client = config.batch_client
+
+        is_master = pick_master.find_master(client)
+
+        if is_master:
+            setup_as_master()
+        else:
+            setup_as_worker()
+    else:
+        print("Action not supported")
+
+
+if __name__ == "__main__":
+    run()

node_scripts/main.sh

@@ -4,6 +4,6 @@ set -ev
 export PATH=/anaconda/envs/py35/bin:$PATH
 
 echo "Starting setup"
-pip install -r requirements.txt
+pip install -r $(dirname $0)/requirements.txt
 echo "Installed dependencies, picking master"
-python pick_master.py
+python $(dirname $0)/main.py install