jaganadhg

SELECT DatabaseName, TableName, SUM(ReadCount) AS TotalReadCount
FROM IDW_STATS_V.IDW_TABLE_USAGE_DETAILS
GROUP BY DatabaseName, TableName
ORDER BY TotalReadCount DESC;


HELP COLUMN IDW_STATS_V.IDW_TABLE_USAGE_DETAILS.*;


SELECT DatabaseName, TableName, SUM(AccessCount) AS TotalAccessCount

jaganadhg

sample = {
  "menu": {
    "id": "file",
    "value": "File",
    "popup": {
      "menuitem": [{
        "value": "New",
        "onclick": "CreateDoc()"
      }, {
        "value": "Open",

jaganadhg

1. https://www.linkedin.com/pulse/deal-shaping-price-to-win-art-superforecasting-keith-irwin-fcpa/
2. https://www.linkedin.com/pulse/20140731053857-19983515-deal-shaping/

jaganadhg

A large hotel reservation company wants to build the next generation hotel reservation and management system specifically tailored to high-end resorts and spas where guests can view and reserve specific rooms.

Users: Guests (hundreds), hotel staff (less than 20)

Requirements:

Registration can be made via web, mobile, phone call, or walk-in. Guests have the ability to either book a type of room (standard, deluxe, or suite) or choose a specific room to stay in by viewing pictures of each room and its location in the hotel.

jaganadhg

• English to Arabic Example-based Machine Translation System Assist. Prof. Suhad M. Kadhem, Yasir R. Nasir IJCCCE Vol.15, No.3, 2015 Paper Cited Man to Machine A tutorial on the art of Machine Translation”, 2010,http://www.slideshare.net/jaganadhg/a-tutorialon-machine-translation

• OpenOffice.org Spell Checkr - http://www.openoffice.org/marketing/conference/foss.in_project_day.html

• Foundation of the Computer Assisted Translation Act - The Online https://www.yumpu.com/en/document/read/43284606/foundation-of-the-computer-assisted-translation-act-the-online- -https://www.tojned.net/journals/tojned/articles/v03i04/v03i04-06.pdf Paper Cited Machine A tutorial on the art of Machine Translation

• Towards Data Mart Building from Social Network for Opinion Analysis (Intelligent Data Engineering and Automated Learning -- IDEAL 2014:)

jaganadhg

jaganadhg

======================= ====================================== ====================================== ================================== ================================== ======================= Codex Assists (Count) Minimum Number of Problems Attempted Maximum Number of Problems Attempted Time Taken to Complete (Minimum) Time Taken to Complete (Maximum) Count of Participants
======================= ====================================== ====================================== ================================== ================================== ======================= 0 5 5 71 81 5
1 5 5 81 89 3
2

jaganadhg

import re

sample_strm = "a%3b%2c:4d:5"

def split_sort_smart(input_str):
    base_list = re.split(r'(\w+%\d+|\w+:\d+)',input_str)

    split_pattern = '|'.join(map(re.escape,['%',':']))

    base_list = [l for l in base_list if len(l) > 0]

jaganadhg

import re

sample_str = "a%3,b%2,c:4,d:5"

def spit_sort(inp_str, delims = ['%',':']):
    base_list = inp_str.split(",")

    split_pattern = '|'.join(map(re.escape,delims))

    print(split_pattern)

jaganadhg

import itertools

base_ip = "1.1.1.1"

ip_max = 3

def gen_ip_smart(base_ip : str) -> list:

    ip_elem = base_ip.split(".")
    ip_elem = list(map(int,ip_elem))