DemianD

SQL languages

DDL is short name of Data Definition Language, which deals with database schemas and descriptions, of how the data should reside in the database.

DML is short name of Data Manipulation Language which deals with data manipulation, and includes most common SQL statements such SELECT, INSERT, UPDATE, DELETE etc, and it is used to store, modify, retrieve, delete and update data in database.

DCL is short name of Data Control Language which includes commands such as GRANT, and mostly concerned with rights, permissions and other controls of the database system.

Datatypes

Text types

DemianD

Keybase proof

I hereby claim:

• I am demiand on github.
• I am demiand (https://keybase.io/demiand) on keybase.
• I have a public key ASCl0yHsfVMbv14wdUU7rkiwb9hIfbBycvG1az7mHkSuKAo

To claim this, I am signing this object:

DemianD

VirtualBox: Set up SSH

Configuration

sudo systemctl enable sshd
sudo systemctl start sshd

sudo systemctl set-default multi-user.target

DemianD

## uccellini

sysctl -w net.ipv4.ip_forward=1

ip l set eth1
ip l set eth2

ifconfig eth1 192.168.9.153 netmask 255.255.255.0
ifconfig eth2 192.168.15.153 netmak 255.255.255.0

DemianD

# Het zijn altijd vierkanten.
$size = 0;

@lijst = ();
%kandidatenLijst = ();

while(<>) {
    chomp;

    @parts = split " ", $_;

DemianD

@ARGV_COPY = @ARGV;

$/ = undef;
$file = <>;

# filtering lines
$file =~ s/.* w$//ms;
$file =~ s/endstream.*//ms;
$_ = $file;

DemianD

Doolhofoefening

Filteren op bruikbare informatie

• filteren op lijnen die eindigen met een w
• lijnen die na endstream komen

Lijnen die ons interesseren

• koppels lijnen die eindigen op m en l
• bevatten coördinaten in pixels die getekend worden

DemianD

#include <math.h>
#include <stdio.h>

float mijn_sinus(float radials) {
  int i = 3;
  float teller = radials;
  int noemer = 1;

  float som = teller / noemer;

DemianD

DemianD

import pyspark
from pyspark.ml.classification import SparkSession
from pyspark.ml.feature import StringIndexer
from pyspark.ml import Pipeline
from pyspark.ml.feature import VectorAssembler
from pyspark.ml.feature import IndexToString
from pyspark.ml.classification import LogisticRegression


spark = SparkSession.builder.appName('pandasToSparkDF').getOrCreate()