pipeline = Pipeline(config) pipe = pipeline.get_or_create_pipe('test_source', source_config) source_file = CsvFile(get_root_path() + '/sample_data/patienten1.csv', delimiter=';') source_file.reflect() source_file.set_primary_key(['patientnummer']) mapping = SourceToSorMapping(source...
were used to support dashboards during the COVID-19 pandemic [17,18,19] to manage the COVID-19 outbreak and obtain insights by modelling and storing the COVID-19 and other related data, thereby focusing on the analytics and leaving behind the previous stage in the data pipeline. Other...
SAP has provided with GW SP04 a basic integration framework for creating an OData service based on the HANA DB. With this framework you can easily expose the HANA
Scenario: We wanted to show how we can upload a csv file to Google cloud storage and then create a table based on it in Big Query and then import this table in SAP Datasphere via Import Remote tables 1) In GCP cloud storage we need to create a bucket Give it a name Next add a la...
The Emitting stage, shown in figure 2.1, is the first stage in your pipeline, where telemetry generated by a production system enters the pipeline. This first stage can be many things:Your production code itself. A logging class inside the production code provides the needed formatting and ...
The pipeline for ALPR involves detecting vehicles in the frame using an object detection deep learning model, localizing the license plate using a license plate detection model, and then finally recognizing the characters on the license plate. Optical character recognition (OCR) using deep neural netw...
Python Másolás from pyspark.ml import Pipeline from pyspark.ml.classification import LogisticRegression from pyspark.ml.feature import HashingTF, Tokenizer from pyspark.sql import Row # The data structure (column meanings) of the data array: # 0 Date # 1 Time # 2 TargetTemp # 3 ActualTemp...