RajenDharmendra RajenDharmendra

MySQL

Getting started

We built this thing to make coding interviews suck less

The traditional technical interview process is designed to ferret out a candidate's weaknesses whereas the process should be designed to find a candidate's strengths.

No one can possibly master all of the arcana of today's technology landscape, let alone bring that mastery to bear on a problem under pressure and with no tools other than a whiteboard.

Under those circumstances, everyone can make anyone look like an idiot.

The fundamental problem with the traditional technical interview process is that it is based on a chain of inference that seems reasonable but is in fact deeply flawed. That chain goes something like this:

	set -o errexit
	TABLE_NAME="${1:?You must pass a TABLE_NAME as first argument}"
	STARTID="${2:?You must pass a STARTID as 2nd argument}"
	ENDID="${3:?You must pass a ENDID as 3rd argument}"
	[[ -z "$4" ]] && LIMIT="" \|\| LIMIT="LIMIT $4"

	. logins.sh

	INSERT_COMMAND="INSERT INTO clickhouse_table(column1,column2,...) FORMAT TSV"

	1、select avg(ss_item_sk) from store_sales;
	2、select ss_sold_Date_sk,count(*) as cnt from store_sales group by ss_sold_Date_sk order by cnt desc,ss_sold_Date_sk limit 10;
	3、select ss_sold_Date_sk,avg(ss_item_sk) as cnt from store_sales group by ss_sold_Date_sk order by cnt desc,ss_sold_Date_sk limit 10;
	4、select ss_item_sk,count() from store_sales group by ss_item_sk having count()>1 limit 10;
	5、select sum(ss_item_sk) from store_sales;
	6、select ss_sold_Date_sk,ss_wholesale_cost,avg(ss_item_sk) as cnt from store_sales group by ss_sold_Date_sk,ss_wholesale_cost order by cnt desc,ss_sold_Date_sk limit 10;
	7、select ss_sold_Date_sk,ss_wholesale_cost,avg(ss_item_sk) as cnt from store_sales group by ss_sold_Date_sk,ss_wholesale_cost order by cnt desc,ss_sold_Date_sk limit 10;

	8、select ss_sold_Date_sk,ss_wholesale_cost,avg(ss_item_sk) as cnt,count(distinct(ss_sales_price)) as avg1 from store_sales group by ss_sold_Date_sk,ss_wholesale_cost order by cnt desc,ss_sold_Date_sk limit 10;

	1、
	select i_item_id,
	avg(cs_quantity) agg1,
	avg(cs_list_price) agg2,
	avg(cs_coupon_amt) agg3,
	avg(cs_sales_price) agg4
	from catalog_sales, customer_demographics, date_dim, item, promotion
	where cs_sold_date_sk = d_date_sk and
	cs_item_sk = i_item_sk and
	cs_bill_cdemo_sk = cd_demo_sk and

	CREATE TABLE tpcdsch.customer_address
	(
	`ca_address_sk` Int8,
	`ca_address_id` String,
	`ca_street_number` String,
	`ca_street_name` String,
	`ca_street_type` String,
	`ca_suite_number` String,
	`ca_city` String,
	`ca_county` String,

	Latency Comparison Numbers (~2012)
	----------------------------------
	L1 cache reference 0.5 ns
	Branch mispredict 5 ns
	L2 cache reference 7 ns 14x L1 cache
	Mutex lock/unlock 25 ns
	Main memory reference 100 ns 20x L2 cache, 200x L1 cache
	Compress 1K bytes with Zippy 3,000 ns 3 us
	Send 1K bytes over 1 Gbps network 10,000 ns 10 us
	Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD

	import anthropic

	client = anthropic.Anthropic(
	api_key="my_api_key",
	)
	message = client.messages.create(
	model="claude-3-opus-20240229",
	max_tokens=1000,
	temperature=0,
	messages=[

RajenDharmendra RajenDharmendra

MySQL

Getting started

Related tutorials

We built this thing to make coding interviews suck less

Slides for Re:Invent conference