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04_​DB_​WritingToDB

04 DB WritingToDB Exercise
Exercise: 04_DB_WritingToDB In this exercise workflow, we connect to the newCensus.sqlite database (SQLite); we read the ss13pme table; we join, filter, and aggregate its data through in-database manipulation; we predict COW values based on all other attributes in the same row; and then we create a timestamp and convert the model fromPMML to table cell. Now: 1. write the original table to ss13pme_original table with a Database Connection Table Writer node ... just in case we mess up with the updates 2. update all rows in the ss13pme table with the output of the predictor node, that is all rows with missing COW value with the predicted COW value, usingcolumn SERIAL NO for WHERE condition (SERIAL NO identifies uniquely each person). Check the UpdateStatus column for success.Optional: Write the learned Decision Tree Model and the timestamp into a new table named "model" newCensus.sqliteselect * from ss13pmeremovePUMA* &PWGTP*COW is not NULLCOW is NULLremove COWCOW to stringappend predictedCOW columnimport all rows where COW is NOT NULLpredict COWimport all rows whereCOW is NULL SQLite Connector DB Table Selector DB Column Filter DB Row Filter DB Row Filter DB Column Filter Number To String Decision TreePredictor DB Reader DecisionTree Learner DB Reader timestamp & model Exercise: 04_DB_WritingToDB In this exercise workflow, we connect to the newCensus.sqlite database (SQLite); we read the ss13pme table; we join, filter, and aggregate its data through in-database manipulation; we predict COW values based on all other attributes in the same row; and then we create a timestamp and convert the model fromPMML to table cell. Now: 1. write the original table to ss13pme_original table with a Database Connection Table Writer node ... just in case we mess up with the updates 2. update all rows in the ss13pme table with the output of the predictor node, that is all rows with missing COW value with the predicted COW value, usingcolumn SERIAL NO for WHERE condition (SERIAL NO identifies uniquely each person). Check the UpdateStatus column for success.Optional: Write the learned Decision Tree Model and the timestamp into a new table named "model" newCensus.sqliteselect * from ss13pmeremovePUMA* &PWGTP*COW is not NULLCOW is NULLremove COWCOW to stringappend predictedCOW columnimport all rows where COW is NOT NULLpredict COWimport all rows whereCOW is NULLSQLite Connector DB Table Selector DB Column Filter DB Row Filter DB Row Filter DB Column Filter Number To String Decision TreePredictor DB Reader DecisionTree Learner DB Reader timestamp & model

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Created by: koetter
Created at: 2015-07-31
On NodePit since: 2020-04-22
Last update: 2024-04-26
Created with KNIME version: v4.4.0
Tags: Big DataEducation

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