Snowflake Container Hierarchy

Data Engineering Simplified
5 min readAug 6, 2023

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This snowflake tutorial, chapter 7, primarily focuses Database, Schema, Table & Container Hierarchy concept and focuses on hands on exercise with table creation, be it standard or external or transient or temporary. It also help with real example of data loading into a table via insert statement, or create as select or insert as select or copy command.

Alongside standard DDL Creation, this chapter also focuses on

  1. Different Data Type while creating tables.
  2. Not Null constraints with field
  3. Case sensitivity with table names.
  4. Describe tables with desc and get_ddl function.
  5. Primary Key & Unique Key constraints in Snowflake tables.
  6. Query External Stage in Snowflake

Check out my courses in Udemy. Popular course include building utility using Snowpark Python API to ingest CSV data as well as JSON data automatically without writing any DDL/DML statement and save 95% of manual effort.

SQL Scripts


-- set context & warehouse
use role sysadmin;

-- create a database
create database my_db
comment = 'this is my demo db';

show databases like 'MY%';


-- as soon as you create the db, the context is changed and current db is set
select current_role(), current_database();


-- create a schema
create schema my_schema
comment = 'this is my demo schema under my_db';

show schemas;

-- as soon as you create the db, the context is changed and current db is set
select current_role(), current_database(), current_schema();

-- you can alternatively create db & schema via Database table a
-- you can also create it using snowsight

-- lets change the context using use sql statement (or via ... function from worksheet)
use database my_db;
use schema my_schema;
select current_role(), current_database(), current_schema();


drop table if exists my_table;
create table my_table (
num number,
num10_1 number(10,1),
decimal_20_2 decimal(20,2),
numeric numeric(30,3),
int int,
integer integer
);

desc table my_table;
--desc table my_db.my_schema.my_table; -- fully qualified name

select get_ddl('table','my_table');

insert into my_table(num,num10_1,decimal_20_2,numeric,int,integer)
values(10,22.2,33.33,123456789,987654321,12112);

-- multiple insert using single statement
insert into my_table(num,num10_1,decimal_20_2,numeric,int,integer)
values (20,22.2,33.33,123456789,987654321,12112), (30,22.2,33.33,123456789,987654321,12112);

select * from my_table;
select * from my_db.my_schema.my_table; -- fully qualified name
select * from "my_db.my_schema.my_table"; -- fully qualified name
select * from "my_db"."my_schema"."my_table"; -- fully qualified name


--
drop table if exists my_text_table;
create table my_text_table (
id int autoincrement,
v varchar,
v50 varchar(50),
c char,
c10 char(10),
s string,
s20 string(20),
t text,
t30 text(30)
);

desc table my_text_table;

insert into my_text_table(v,v50,c,c10,s,s20,t,t30)
values('a','b','c','d','e','f','g','h');

-- lets load data using webui
select * from my_text_table;

-- boolean data set
create or replace table my_boolean_table(
b boolean,
n number,
s string);

desc table my_boolean_table;

insert into my_boolean_table values (true, 1, 'yes'), (false, 0, 'no'), (null, null, null);
select * from my_boolean_table;

-- time stamp table
drop table if exists my_ts_tablel;
create or replace table my_ts_table(
today_date date default current_date(),
now_time time default current_time(),
now_ts timestamp default current_timestamp()
);

-- lets desc the table
desc table my_ts_table;

-- insert one record
insert into my_ts_table (today_date,now_time,now_ts) values (current_date, current_time,current_timestamp);
insert into my_ts_table (now_time,now_ts) values (current_time,current_timestamp);

-- now select the data
select * from my_ts_table;

-- change the session level timezone and see the result
alter session set timezone = 'America/Los_Angeles';
alter session set timezone = 'Japan';
alter session set timestamp_output_format = 'YYYY-MM-DD HH24:MI:SS.FF';


// ====================================================================
-- Upper, Lower & Mixed case table
drop table my_case_table;
create table my_case_table (my_field string);
desc table my_case_table;
show tables like 'MY_C%';
create table MY_CASE_TABLE (my_field string);
create table my_CASE_TABLE (my_field string);

-- run show tables command
show tables;

// ====================================================================
-- Object Identifier
create table "my table" (my_field string);
create table "My Table" ("my field" string);
create table "MY TABLE" ("my field" string, "My Field" string);

show tables;
desc table "my table";
desc table "MY TABLE" ;


// ====================================================================
-- Create table as select
create table my_ctas as select * from my_db.my_schema.my_table;

select * from my_ctas;

-- Load data using select as statement
insert into my_ctas (num ,num10_1, decimal_20_2 ,numeric,int ,integer)
select
num ,num10_1, decimal_20_2 ,numeric,int ,integer
from
my_db.my_schema.my_table;

-- load data via web interface
-- load a csv file

// =====================================================================
-- lets quickly understand the const
drop table if exists my_constaints_table;
create table my_constaints_table (
emp_pk string primary key,
fname string not null,
lname string not null,
flag string default 'active',
unique_code string unique
);

insert into my_constaints_table (emp_pk,fname,lname,unique_code)
values ('100','John1','K','1000'),
('100','John2','K','1000');

select * from my_constaints_table;

-- below throws error as PK is missing
insert into my_constaints_table (fname,lname,unique_code)
values ('John3','K','1000');

-- below throws error as non-null column value is missing
insert into my_constaints_table (emp_pk,fname,unique_code)
values (100,'John4','1000');

-- so you have to take care of PK and Uniqueness, only Not-null is applifed

// =========================================================

-- put file:///tmp/ch07.csv @my_stg;

list @my_stg;

/* sample data
100,22.2,33.33,123456789,987654321,12112
200,22.2,33.33,123456789,987654321,12112
300,22.2,33.33,123456789,987654321,12112
*/

-- list the stage
list @ch7_stg;

-- lets view the data first
create or replace file format my_format type = 'csv' field_delimiter = ',';
select t.$1, t.$2, t.$3,t.$4, t.$5, t.$6 from @my_stg (file_format => 'my_format') t;

-- now we can use copy command to load data

drop table if exists my_stg_table;
create table my_stg_table (
num number,
num10_1 number(10,1),
decimal_20_2 decimal(20,2),
numeric numeric(30,3),
int int,
integer integer
);

-- lets check data
select * from my_stg_table;

-- now load data via copy command
copy into my_stg_table
from @my_stg;

-- lets check data
select * from my_stg_table;

-- create using ctas
create table my_ctas_big_table as select * from "SNOWFLAKE_SAMPLE_DATA"."TPCH_SF100"."ORDERS";

-- change the time travel to 30 days;
alter table my_ctas_big_table set data_retention_time_in_days=30;

-- lets check the table before update
select * from my_ctas_big_table limit 10;

-- lets change the status
select O_ORDERSTATUS,count(1) from my_ctas_big_table group by O_ORDERSTATUS;

-- update the data and see the storage cost now
update my_ctas_big_table set O_ORDERSTATUS ='o' where O_ORDERSTATUS = 'O';

select count(*) from my_ctas_big_table before (statement => '019f0d45-0b01-d7c5-0000-0001acbea735')
where O_ORDERSTATUS = 'O';

select count(*) from my_ctas_big_table where O_ORDERSTATUS = 'P';


//=======================================
-- Variant Data
create table json_weather_data (v variant);
desc table json_weather_data;

create stage nyc_weather
url = 's3://snowflake-workshop-lab/weather-nyc';

-- list wheather
list @nyc_weather;

-- copy from external stage
copy into json_weather_data
from @nyc_weather
file_format = (type=json);

-- select data
select * from json_weather_data limit 10;

-- create a view
create view json_weather_data_view as
select
v:time::timestamp as observation_time,
v:city.id::int as city_id,
v:city.name::string as city_name,
v:city.country::string as country,
v:city.coord.lat::float as city_lat,
v:city.coord.lon::float as city_lon,
v:clouds.all::int as clouds,
(v:main.temp::float)-273.15 as temp_avg,
(v:main.temp_min::float)-273.15 as temp_min,
(v:main.temp_max::float)-273.15 as temp_max,
v:weather[0].main::string as weather,
v:weather[0].description::string as weather_desc,
v:weather[0].icon::string as weather_icon,
v:wind.deg::float as wind_dir,
v:wind.speed::float as wind_speed
from json_weather_data
where city_id = 5128638;

select * from json_weather_data_view;

-- create external table
create or replace external table json_weather_data_et (
time varchar AS (value:c1::varchar),
....

)
with location=@nyc_weather
auto_refresh = false
file_format = (format_name = file_format)
;


// =======================================
-- Temp & Transitent table

// create a transitent table
create transitent table json_weather_data (v variant);

// create a temporaty table
create temporary table json_weather_data (v variant);

--

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Data Engineering Simplified
Data Engineering Simplified

Written by Data Engineering Simplified

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