Add testws11/main.py.notebook, testws11/main.py, testws11/main.workflow

testws11/main.py

@@ -0,0 +1,115 @@
+
+__generated_with = "0.13.15"
+
+# %%
+
+import sys
+import time
+from pyspark.sql.utils import AnalysisException
+sys.path.append('/opt/spark/work-dir/')
+from workflow_templates.spark.udf_manager import bootstrap_udfs 
+from util import get_logger, observe_metrics, collect_metrics, log_info, log_error, forgiving_serializer
+from pyspark.sql.functions import udf 
+from pyspark.sql.functions import count, expr, lit
+from pyspark.sql.types import StringType, IntegerType
+import uuid
+from pathlib import Path
+from pyspark import SparkConf, Row
+from pyspark.sql import SparkSession
+from pyspark.sql.observation import Observation
+from pyspark import StorageLevel
+import os
+import pandas as pd
+import polars as pl
+import pyarrow as pa
+from pyspark.sql.functions import approx_count_distinct, avg, collect_list, collect_set, corr, count, countDistinct, covar_pop, covar_samp, first, kurtosis, last, max, mean, min, skewness, stddev, stddev_pop, stddev_samp, sum, var_pop, var_samp, variance,expr,to_json,struct, date_format, col, lit, when, regexp_replace, ltrim
+from functools import reduce
+from handle_structs_or_arrays import preprocess_then_expand
+import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util.retry import Retry
+from jinja2 import Template
+import json
+
+
+from secrets_manager import SecretsManager
+
+from WorkflowManager import WorkflowDSL, WorkflowManager
+from KnowledgebaseManager import KnowledgebaseManager
+from gitea_client import GiteaClient, WorkspaceVersionedContent
+from FilesystemManager import FilesystemManager, SupportedFilesystemType
+from Materialization import Materialization
+
+from dremio.flight.endpoint import DremioFlightEndpoint
+from dremio.flight.query import DremioFlightEndpointQuery
+
+init_start_time=time.time()
+
+LOGGER = get_logger()
+alias_str='abcdefghijklmnopqrstuvwxyz'
+workspace = os.getenv('WORKSPACE') or 'test_charan'
+workflow = 'testws11'
+execution_environment = os.getenv('EXECUTION_ENVIRONMENT') or 'CLUSTER'
+
+job_id = os.getenv("EXECUTION_ID") or str(uuid.uuid4())
+retry_job_id = os.getenv("RETRY_EXECUTION_ID") or ''
+
+log_info(LOGGER, f"Workspace: '{workspace}', Workflow: '{workflow}', Execution Environment: '{execution_environment}', Job Id: '{job_id}', Retry Job Id: '{retry_job_id}'")
+
+sm = SecretsManager(os.getenv('SECRET_MANAGER_URL'), os.getenv('SECRET_MANAGER_NAMESPACE'), os.getenv('SECRET_MANAGER_ENV'), os.getenv('SECRET_MANAGER_TOKEN'))
+secrets = sm.list_secrets(workspace)
+
+gitea_client=GiteaClient(os.getenv('GITEA_HOST'), os.getenv('GITEA_TOKEN'), os.getenv('GITEA_OWNER') or 'gitea_admin', os.getenv('GITEA_REPO') or 'tenant1')
+workspaceVersionedContent=WorkspaceVersionedContent(gitea_client)
+
+filesystemManager = FilesystemManager.create(secrets.get('LAKEHOUSE_BUCKET'), storage_options={'key': secrets.get('S3_ACCESS_KEY'), 'secret': secrets.get('S3_SECRET_KEY'), 'region': secrets.get('S3_REGION')})
+if retry_job_id:
+    logs = Materialization.get_execution_history_by_job_id(filesystemManager, secrets.get('LAKEHOUSE_BUCKET'), workspace, workflow, retry_job_id, selected_components=['finalize']).to_dicts()
+    if len(logs) == 1 and logs[0].get('metrics').get('execute_status') == 'SUCCESS':
+        log_info(LOGGER, f"Workspace: '{workspace}', Workflow: '{workflow}', Execution Environment: '{execution_environment}', Job Id: '{job_id}' - Retry Job Id: '{retry_job_id}' was already successful. Hence exiting to forward processing to next in chain.")
+        sys.exit(0)
+
+_conf = SparkConf()
+_params = {
+ "spark.hadoop.fs.s3a.access.key": secrets.get(''),
+ "spark.hadoop.fs.s3a.secret.key": secrets.get(''),
+ "spark.hadoop.fs.s3a.aws.region": secrets.get("S3_REGION") or "",
+ "spark.sql.catalog.dremio.warehouse" : secrets.get('LAKEHOUSE_BUCKET'),
+ "spark.hadoop.fs.s3a.aws.credentials.provider": "com.amazonaws.auth.DefaultAWSCredentialsProviderChain",
+ "spark.hadoop.fs.s3.aws.credentials.provider": "com.amazonaws.auth.DefaultAWSCredentialsProviderChain",
+ "spark.sql.catalog.dremio" : "org.apache.iceberg.spark.SparkCatalog",
+ "spark.sql.catalog.dremio.type" : "hadoop",
+ "spark.hadoop.fs.s3a.impl": "org.apache.hadoop.fs.s3a.S3AFileSystem",
+ "spark.hadoop.fs.s3.impl": "org.apache.hadoop.fs.s3a.S3AFileSystem",
+ "spark.hadoop.fs.gs.impl": "com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem",
+ "spark.sql.extensions": "org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions",
+ "spark.jars.packages": "com.amazonaws:aws-java-sdk-bundle:1.12.262,com.github.ben-manes.caffeine:caffeine:3.2.0,org.apache.iceberg:iceberg-aws-bundle:1.8.1,org.apache.iceberg:iceberg-common:1.8.1,org.apache.iceberg:iceberg-core:1.8.1,org.apache.iceberg:iceberg-spark:1.8.1,org.apache.hadoop:hadoop-aws:3.3.4,com.amazonaws:aws-java-sdk-bundle:1.11.901,org.apache.hadoop:hadoop-common:3.3.4,org.apache.hadoop:hadoop-cloud-storage:3.3.4,org.apache.hadoop:hadoop-client-runtime:3.3.4,org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.8.1,org.projectnessie.nessie-integrations:nessie-spark-extensions-3.5_2.12:0.103.2,org.apache.spark:spark-sql-kafka-0-10_2.12:3.5.2,za.co.absa.cobrix:spark-cobol_2.12:2.8.0,ch.cern.sparkmeasure:spark-measure_2.12:0.26"
+}
+
+
+
+_conf.setAll(list(_params.items()))
+
+spark = SparkSession.builder.appName(workspace).config(conf=_conf).getOrCreate()
+bootstrap_udfs(spark)
+
+materialization = Materialization(spark, secrets.get('LAKEHOUSE_BUCKET'), workspace, workflow, job_id, retry_job_id, execution_environment, LOGGER)
+
+init_dependency_key="init"
+
+
+init_end_time=time.time()
+
+# %%
+
+finalize_start_time=time.time()
+
+metrics = {
+    'data': collect_metrics(locals()),
+}
+materialization.materialized_execution_history({'finalize': {'execute_status': 'SUCCESS', 'fail_on_error': 'False'}, **metrics['data']})
+log_info(LOGGER, f"Workflow Data metrics: {metrics['data']}")
+
+finalize_end_time=time.time()
+
+spark.stop()