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-- podnies place pracownikow ktorzy maja wiecej niz 2 kleintow
-- GIT GUCCI
--UPDATE PRACOWNICY xd
--SET xd.PENSJA = xd.PENSJA*1.2
--WHERE (SELECT COUNT(ID_KLIENTA) FROM KLIENCI WHERE xd.ID_PRACOWNIKA = KLIENCI.ID_PRACOWNIKA GROUP BY xd.ID_PRACOWNIKA) > 2;
-- wyswietlic max i min zamowien dla poszcz klientow
-- GUCCI
--SELECT KLIENCI.NAZWA, COALESCE(MIN(ZAMOWIENIA.WARTOSC), 0), COALESCE(MAX(ZAMOWIENIA.WARTOSC), 0)
--FROM ZAMOWIENIA
@rmitula
rmitula / gist:2b56c7aa7c7a39c6297e1b3a4e6da9f3
Created July 31, 2018 20:44 — forked from psayre23/gist:c30a821239f4818b0709
Runtime Complexity of Java Collections
Below are the Big O performance of common functions of different Java Collections.
List | Add | Remove | Get | Contains | Next | Data Structure
---------------------|------|--------|------|----------|------|---------------
ArrayList | O(1) | O(n) | O(1) | O(n) | O(1) | Array
LinkedList | O(1) | O(1) | O(n) | O(n) | O(1) | Linked List
CopyOnWriteArrayList | O(n) | O(n) | O(1) | O(n) | O(1) | Array
{
"title": "Turniej Milosci2",
"description": "Tutaj powinien znajdowac sie szczegolowy opis turnieju",
"city": "RZESZOW",
"maxPlayers": 4,
"eliminationType": "ROUND_ROBIN",
"state": "PENDING",
"access": "OPEN",
"startDate": "2018-09-01",
"endDate": null,
// Future versions of Hyper may add additional config options,
// which will not automatically be merged into this file.
// See https://hyper.is#cfg for all currently supported options.
module.exports = {
config: {
hyperTabs: {
closeAlign: 'right',
activityColor: 'salmon',
@rmitula
rmitula / data.json
Last active July 28, 2023 07:20
Listing 1. Sample products records are stored in the Raw Data Zone under /day=01 partition
{
"product_id": "29e17633-8d1e-4d63-8291-7a34fd79a4e5",
"name": "Product A",
"category": "Electronics",
"variants": [
{
"color": "black",
"size": "M",
"stock": 100
},
@rmitula
rmitula / gist:ca4ef3c80ffcd61043901309291dd966
Created July 28, 2023 07:22
Listing 2. Amazon S3 Bucket structure under Raw Data Zone
raw-zone/
└── products/
└── year=2023/
└── month=05/
├── day=01/
| └── data.json
├── day=02/
| └── data.json
└── (...)
└── (...)
@rmitula
rmitula / job.py
Created July 28, 2023 07:23
Listing 3. Sample Python script in AWS Glue Job leverages Apache Spark to transform JSON data from the Raw Data Zone into Apache Iceberg format in the Curated Data Zone, simultaneously updating the AWS Glue Data Catalog
import sys
import boto3
from pyspark.sql.functions import concat_ws, lpad
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
# Initialize Spark and Glue context
@rmitula
rmitula / gist:8958982dd7c5c54b425ac6012b5695e8
Created July 28, 2023 07:25
Listing 3. Amazon S3 Bucket structure under Curated Data Zone
curated-zone/
└── products/
├── data/
│ └── 00000-(...)-00001.parquet
└── metadata/
├── 00000-(...)-7c99bf9d1216.metadata.json
├── 5b9bf671-(...)-06c3dd2fe777.avro
@rmitula
rmitula / data.json
Created July 28, 2023 07:26
Listing 5. Updated products record of Product A stored in the Raw Data Zone under /day=02 partition.
{
"product_id": "29e17633-8d1e-4d63-8291-7a34fd79a4e5",
"name": "Product A",
"category": "Electronics",
"variants": [
{
"color": "black",
"size": "M",
"stock": 100
},