pietheinstrengholt

JQFEED = {
	numNews: 5,
	appendTo: '#blogfeed',
	realUrl: 'http://www.perry.es',
	internalUrl: '/blog_feed',
	loadFeeds: function() {
		$(JQFEED.appendTo).html('Loading feed...');
        $.ajax({
            url: JQFEED.internalUrl,
            type: 'GET',

pietheinstrengholt

#!/bin/sh

# Converts a mysqldump file into a Sqlite 3 compatible file. It also extracts the MySQL `KEY xxxxx` from the
# CREATE block and create them in separate commands _after_ all the INSERTs.

# Awk is choosen because it's fast and portable. You can use gawk, original awk or even the lightning fast mawk.
# The mysqldump file is traversed only once.

# Usage: $ ./mysql2sqlite mysqldump-opts db-name | sqlite3 database.sqlite
# Example: $ ./mysql2sqlite --no-data -u root -pMySecretPassWord myDbase | sqlite3 database.sqlite

pietheinstrengholt

<?php
/**
 * ODBC for DBO
 *
 * PHP versions 4 and 5
 *
 * CakePHP(tm) : Rapid Development Framework (http://cakephp.org)
 * Copyright 2005-2009, Cake Software Foundation, Inc. (http://cakefoundation.org)
 *
 * Licensed under The MIT License

pietheinstrengholt

<?php
/**
 * ODBC layer for DBO
 * Helpful for Linux connection to MS SQL Server via FreeTDS
 *
 * PHP 5
 *
 * CakePHP(tm) : Rapid Development Framework (http://cakephp.org)
 * Copyright 2005-2012, Cake Software Foundation, Inc. (http://cakefoundation.org)
 *

pietheinstrengholt

%%pyspark

schema = StructType([
    StructField("src_Id", IntegerType(), True),
    StructField("src_Firstname", StringType(), True),
    StructField("src_Lastname", StringType(), True),
    StructField("src_CreatedAt", DateType(), True),
    StructField("src_Department", StringType(), True),
    StructField("src_Salary", StringType(), True)
    ]

pietheinstrengholt

current_date = datetime.today().date()
print(current_date)

# Prepare for merge - Added effective and end date
df_source_new = dfDataChanged.withColumn('src_current', lit(True)).withColumn('src_effectiveDate', lit(current_date)).withColumn('src_endDate', lit(None))
df_source_new.show()

# FULL Merge, join on key column and also high date column to make only join to the latest records
df_merge = dfDataOriginal.join(df_source_new, (df_source_new.src_Id == dfDataOriginal.Id), how='fullouter')

pietheinstrengholt

{
    "enumDefs": [],
    "structDefs": [],
    "classificationDefs": [],
    "entityDefs": [
        {
            "name": "data_landing_zone",
            "description": "Data Landing Zone",
            "createdBy": "admin",
            "updatedBy": "admin",

pietheinstrengholt

{
    "entity": {
        "status": "ACTIVE",
        "createTime": 1592928847,
        "updateTime": 1594120997,
        "createdBy": "Superadmin",
        "version": 1,
        "attributes": {
            "name": "SalesLTAddress",
            "db": {

pietheinstrengholt

%%pyspark

from pyspark import *
from pyspark.sql.window import Window
from pyspark.sql.functions import *
from pyspark.sql import Row
from pyspark.sql.types import StructType, StructField, IntegerType, StringType, TimestampType, BooleanType, DateType
from typing import List
from datetime import datetime

pietheinstrengholt

%%pyspark

from datetime import date
current_date = datetime.today().date()

try:
    # Read original data - this is your scd type 2 table holding all data
    dataOriginal = spark.read.load(dfDataOriginalPath + "/" + cw_database + "/" + cw_table, format='delta')
except:
    # Use first load when no data exists yet