From 32b20808b6758899aeb12a2ddd41cf8acddbe1f6 Mon Sep 17 00:00:00 2001
From: Dominik Hoffmann <dominik151099@outlook.de>
Date: Tue, 26 Nov 2024 11:46:17 +0100
Subject: [PATCH] Revert "#26 Hotfix: Switched to correct pyspark DF format"

This reverts commit 673afa8309c831f529a0ea8f8f0fb47b6a5f6b0e.
---
 .../spark/dataframe/dataframe_log_handler.py  | 23 +++++--------------
 .../pipelines/logging/test_log_collection.py  |  8 +++----
 2 files changed, 10 insertions(+), 21 deletions(-)

diff --git a/src/sdk/python/rtdip_sdk/pipelines/logging/spark/dataframe/dataframe_log_handler.py b/src/sdk/python/rtdip_sdk/pipelines/logging/spark/dataframe/dataframe_log_handler.py
index 66024643f..cb8af94fc 100644
--- a/src/sdk/python/rtdip_sdk/pipelines/logging/spark/dataframe/dataframe_log_handler.py
+++ b/src/sdk/python/rtdip_sdk/pipelines/logging/spark/dataframe/dataframe_log_handler.py
@@ -14,12 +14,9 @@
 import logging
 
 import pandas
-
+from pandas import DataFrame
 from datetime import datetime
 
-from pyspark.sql import DataFrame, SparkSession
-from pyspark.sql.types import StructType, StructField, StringType, DateType
-
 
 class DataFrameLogHandler(logging.Handler):
     """
@@ -41,19 +38,9 @@ class DataFrameLogHandler(logging.Handler):
     """
 
     logs_df: DataFrame = None
-    spark = None
 
     def __init__(self):
-        self.spark = SparkSession.builder.appName("Dataframe Log Handler").getOrCreate()
-        df_schema = StructType(
-            [
-                StructField("timestamp", DateType(), True),
-                StructField("name", StringType(), True),
-                StructField("level", StringType(), True),
-                StructField("message", StringType(), True),
-            ]
-        )
-        self.logs_df = self.spark.createDataFrame([], schema=df_schema)
+        self.logs_df = DataFrame(columns=["timestamp", "name", "level", "message"])
         super().__init__()
 
     def emit(self, record: logging.LogRecord) -> None:
@@ -65,8 +52,10 @@ def emit(self, record: logging.LogRecord) -> None:
             "message": record.msg,
         }
 
-        new_log_df_row = self.spark.createDataFrame([log_entry])
-        self.logs_df = self.logs_df.union(new_log_df_row)
+        new_log_df_row = pandas.DataFrame(
+            log_entry, columns=["timestamp", "name", "level", "message"], index=[0]
+        )
+        self.logs_df = pandas.concat([self.logs_df, new_log_df_row], ignore_index=True)
 
     def get_logs_as_df(self) -> DataFrame:
         return self.logs_df
diff --git a/tests/sdk/python/rtdip_sdk/pipelines/logging/test_log_collection.py b/tests/sdk/python/rtdip_sdk/pipelines/logging/test_log_collection.py
index e2157cb9c..89fd77b7e 100644
--- a/tests/sdk/python/rtdip_sdk/pipelines/logging/test_log_collection.py
+++ b/tests/sdk/python/rtdip_sdk/pipelines/logging/test_log_collection.py
@@ -14,7 +14,7 @@
 import os
 
 import pytest
-from pyspark.sql import DataFrame
+from pandas import DataFrame
 from pyspark.sql import SparkSession
 
 from src.sdk.python.rtdip_sdk.pipelines.logging.spark.runtime_log_collector import (
@@ -38,8 +38,8 @@ def spark():
     spark.stop()
 
 
-def test_logger_manager_basic_function(spark):
-    df = spark.createDataFrame([(1, "2024-02-11 00:00:00.000")], ["Index", "EventTime"])
+def test_logger_manager_basic_function():
+    df = DataFrame()
     monitor = IdentifyMissingDataInterval(
         df=df,
         interval="10s",
@@ -78,7 +78,7 @@ def test_df_output(spark, caplog):
 
     result_df = log_collector.get_logs_as_df()
 
-    assert result_df.count() == 6
+    assert result_df.shape[0] == 6
 
 
 def test_file_logging(spark, caplog):