Quick Start
A Walk-Through Example
Let's start with a simple example. If you haven't installed wv command, install wvlet command to your machine. wv command starts an interactive shell, which is backed by DuckDB in-memory database by default.
For the ease of learning, let's create a sample TPC-H benchmark data set:
$ wv
wv> execute sql"call dbgen(sf=0.01)";
wv> show tables;
┌────────────┐
│ table_name │
│ string │
├────────────┤
│ customer │
│ lineitem │
│ nation │
│ orders │
│ part │
│ partsupp │
│ region │
│ supplier │
├────────────┤
│ 8 rows │
└────────────┘
The above execute sql"call dbgen(sf=0.01)" command calls DuckDB's TPC-H extension and creates an in-memory TPC-H benchmark database, which will be gone when you exit the wvlet shell. So you can try this command without worrying about the disk space.
The simplest form of queries is from (table name):
wv> from customer;
┌───────────┬────────────────────┬─────────────────────────────────────────┬───────────>
│ c_custkey │ c_name │ c_address │ c_nationke>
│ long │ string │ string │ int >
├───────────┼────────────────────┼─────────────────────────────────────────┼───────────>
│ 1 │ Customer#000000001 │ j5JsirBM9PsCy0O1m │ 1>
│ 2 │ Customer#000000002 │ 487LW1dovn6Q4dMVymKwwLE9OKf3QG │ 1>
│ 3 │ Customer#000000003 │ fkRGN8nY4pkE │ >
│ 4 │ Customer#000000004 │ 4u58h fqkyE │ >
│ 5 │ Customer#000000005 │ hwBtxkoBF qSW4KrIk5U 2B1AU7H │ >
│ 6 │ Customer#000000006 │ g1s,pzDenUEBW3O,2 pxu0f9n2g64rJrt5E │ 2>
│ 7 │ Customer#000000007 │ 8OkMVLQ1dK6Mbu6WG9 w4pLGQ n7MQ │ 1>
│ 8 │ Customer#000000008 │ j,pZ,Qp,qtFEo0r0c 92qobZtlhSuOqbE4JGV │ 1>
│ 9 │ Customer#000000009 │ vgIql8H6zoyuLMFNdAMLyE7 H9 │ >
This query returns all the columns in the customer table.
If the query result doesn't fit to the screen, wvlet shell enters UNIX less command mode, which
allows to navigate table data using arrow keys, page up/down keys, and q key to exit the mode. See Interactive Shell for the list of the available shortcut keys.
To limit the number of rows to display, you can use limit operator:
wv> from customer
│ limit 3;
┌───────────┬────────────────────┬────────────────────────────────┬─────────────┬──────>
│ c_custkey │ c_name │ c_address │ c_nationkey │ c>
│ long │ string │ string │ int │ s>
├───────────┼────────────────────┼────────────────────────────────┼─────────────┼──────>
│ 1 │ Customer#000000001 │ j5JsirBM9PsCy0O1m │ 15 │ 25-98>
│ 2 │ Customer#000000002 │ 487LW1dovn6Q4dMVymKwwLE9OKf3QG │ 13 │ 23-76>
│ 3 │ Customer#000000003 │ fkRGN8nY4pkE │ 1 │ 11-71>
├───────────┴────────────────────┴────────────────────────────────┴─────────────┴──────>
│ 3 rows >
└──────────────────────────────────────────────────────────────────────────────────────>
Separators | between expressions are shown only while editing queries. You don't need to type | in the wvlet shell or in query files.
To select specific columns, you can use select operator:
from customer
wv> from customer
│ select c_name, c_nationkey
│ limit 5;
┌────────────────────┬─────────────┐
│ c_name │ c_nationkey │
│ string │ int │
├────────────────────┼─────────────┤
│ Customer#000000001 │ 15 │
│ Customer#000000002 │ 13 │
│ Customer#000000003 │ 1 │
│ Customer#000000004 │ 4 │
│ Customer#000000005 │ 3 │
├────────────────────┴─────────────┤
│ 5 rows │
└──────────────────────────────────┘
To select specific values from the table, you can use where operator:
wv> from customer
│ where c_nationkey = 1
│ select c_name, c_address
│ limit 5;
┌────────────────────┬─────────────┐
│ c_name │ c_nationkey │
│ string │ int │
├────────────────────┼─────────────┤
│ Customer#000000003 │ 1 │
│ Customer#000000014 │ 1 │
│ Customer#000000030 │ 1 │
│ Customer#000000059 │ 1 │
│ Customer#000000106 │ 1 │
├────────────────────┴─────────────┤
│ 5 rows │
└──────────────────────────────────┘
Writing Queries
One-Liner Queries
In wvlet, individual query line often matches with a single relational operator, which processes a given input table data and return a new table data. Inserting newlines, however, is not mandatory. You can fit the whole query within a single line, which is convenient for quick data exploration:
wv> from customer where c_mktsegment = 'HOUSEHOLD' limit 5;
┌───────────┬────────────────────┬────────────────────────────────────────┬────────────>
│ c_custkey │ c_name │ c_address │ c_nationkey>
│ long │ string │ string │ int >
├───────────┼────────────────────┼────────────────────────────────────────┼────────────>
│ 5 │ Customer#000000005 │ hwBtxkoBF qSW4KrIk5U 2B1AU7H │ 3>
│ 10 │ Customer#000000010 │ Vf mQ6Ug9Ucf5OKGYq fsaX AtfsO7,rwY │ 5>
│ 12 │ Customer#000000012 │ Sb4gxKs7W1AZa │ 13>
│ 15 │ Customer#000000015 │ 3y4KK4CcfNwNCTP0u0p1Rk6aeghe3Z30mo0VnD │ 23>
│ 19 │ Customer#000000019 │ yO0XPkiuSWk0vN FfcH5 IA3oBYy │ 18>
├───────────┴────────────────────┴────────────────────────────────────────┴────────────>
│ 5 rows >
└──────────────────────────────────────────────────────────────────────────────────────>
Adding Comments
The multi-line syntax is convenient for improving readability of your queries. As Wvlet adopts a flow-style syntax, you can add comments to each line of the query:
wv> from customer
│ -- Select customers for each market segment, e.g., HOUSEHOLD, BUILDING, etc.
│ group by c_mktsegment,
│ -- Report the number of customers in each market segment
│ agg _.count as customer_count
┌──────────────┬────────────────┐
│ c_mktsegment │ customer_count │
│ string │ long │
├──────────────┼────────────────┤
│ HOUSEHOLD │ 588 │
│ BUILDING │ 674 │
│ MACHINERY │ 576 │
│ FURNITURE │ 558 │
│ AUTOMOBILE │ 604 │
├──────────────┴────────────────┤
│ 5 rows │
└───────────────────────────────┘
Comments in wvlet start with -- and continue to the end of the line.
Exploring Data
Describing Table Schema
To learn about the table schema, the list of columns and types in the table, you can use describe operator:
wv> from customer
│ describe;
┌──────────────┬─────────────┐
│ column_name │ column_type │
│ string │ string │
├──────────────┼─────────────┤
│ c_custkey │ long │
│ c_name │ string │
│ c_address │ string │
│ c_nationkey │ int │
│ c_phone │ string │
│ c_acctbal │ decimal │
│ c_mktsegment │ string │
│ c_comment │ string │
├──────────────┴─────────────┤
│ 8 rows │
└────────────────────────────┘
describe is also a relational operator, which can be filtered by where operator:
wv> from customer
│ describe
│ where column_name like '%name%';
┌─────────────┬─────────────┐
│ column_name │ column_type │
│ string │ string │
├─────────────┼─────────────┤
│ c_name │ string │
├─────────────┴─────────────┤
│ 1 rows │
└───────────────────────────┘
Quick Schema Check
A more convenient way to see the table schema is to use ctrl-j ctrl-d shortcut keys in the wvlet shell:
describe (line:1): from customer
┌──────────────┬─────────────┐
│ column_name │ column_type │
│ string │ string │
├──────────────┼─────────────┤
│ c_custkey │ long │
│ c_name │ string │
│ c_address │ string │
│ c_nationkey │ int │
│ c_phone │ string │
│ c_acctbal │ decimal │
│ c_mktsegment │ string │
│ c_comment │ string │
├──────────────┴─────────────┤
│ 8 rows │
└────────────────────────────┘
wv> from customer -- Press ctrl-j ctrl-d sequence here
│ where c_nationkey = 1
│ select c_name, c_nationkey
│ limit 5;
ctrl-j ctrl-d shortcut key internally calls (A query fragment up to the current line) describe to show the schema of the current query fragment.
You can also check the schema in the middle of a query:
describe (line:3): select c_name, c_nationkey
┌─────────────┬─────────────┐
│ column_name │ column_type │
│ string │ string │
├─────────────┼─────────────┤
│ c_name │ string │
│ c_nationkey │ int │
├─────────────┴─────────────┤
│ 2 rows │
└───────────────────────────┘
wv> from customer
│ where c_nationkey = 1
│ select c_name, c_nationkey -- Press ctrl-j ctrl-d here
│ limit 5;
Test Run to Peek Data
While editing queries, you will often need to look at the actual data. Type ctrl-j ctrl-t (test run) to see the intermediate query results at the line:
wv> from customer -- type ctrl-j ctrl-t here
│ where c_nationkey = 1
│ select c_name, c_nationkey
│ limit 5;
debug (line:1): from customer
┌───────────┬────────────────────┬─────────────────────────────────────────┬───────────>
│ c_custkey │ c_name │ c_address │ c_nationke>
│ long │ string │ string │ int >
├───────────┼────────────────────┼─────────────────────────────────────────┼───────────>
│ 1 │ Customer#000000001 │ j5JsirBM9PsCy0O1m │ 1>
│ 2 │ Customer#000000002 │ 487LW1dovn6Q4dMVymKwwLE9OKf3QG │ 1>
│ 3 │ Customer#000000003 │ fkRGN8nY4pkE │ >
│ 4 │ Customer#000000004 │ 4u58h fqkyE │ >
│ 5 │ Customer#000000005 │ hwBtxkoBF qSW4KrIk5U 2B1AU7H │ >
│ 6 │ Customer#000000006 │ g1s,pzDenUEBW3O,2 pxu0f9n2g64rJrt5E │ 2>
│ 7 │ Customer#000000007 │ 8OkMVLQ1dK6Mbu6WG9 w4pLGQ n7MQ │ 1>
│ 8 │ Customer#000000008 │ j,pZ,Qp,qtFEo0r0c 92qobZtlhSuOqbE4JGV │ 1>
│ 9 │ Customer#000000009 │ vgIql8H6zoyuLMFNdAMLyE7 H9 │ >
│ 10 │ Customer#000000010 │ Vf mQ6Ug9Ucf5OKGYq fsaX AtfsO7,rwY │ >
Test run command is useful to refine your query as you add more relational operators:
wv> from customer
│ select c_custkey, c_name, c_nationkey -- type ctrl-j ctrl-t here
debug (line:2): select c_custkey, c_name, c_nationkey
┌───────────┬────────────────────┬─────────────┐
│ c_custkey │ c_name │ c_nationkey │
│ long │ string │ int │
├──── ───────┼────────────────────┼─────────────┤
│ 1 │ Customer#000000001 │ 15 │
│ 2 │ Customer#000000002 │ 13 │
│ 3 │ Customer#000000003 │ 1 │
│ 4 │ Customer#000000004 │ 4 │
│ 5 │ Customer#000000005 │ 3 │
│ 6 │ Customer#000000006 │ 20 │
Reusing Queries
In wvlet, you can name a query using select as operator, and refer to the named query result in the subsequent queries:
wv> from customer
│ where c_nationkey = 1
│ -- Name the query as domestic_customer
│ select as domestic_customer;
You can refer to the named query result in the subsequent queries:
wv> from domestic_customer
│ limit 5;
┌───────────┬────────────────────┬─────────────────────────────────────────┬─────────────┬─>
│ c_custkey │ c_name │ c_address │ c_nationkey │ >
│ long │ string │ string │ int │ >
├───────────┼────────────────────┼─────────────────────────────────────────┼─────────────┼─>
│ 3 │ Customer#000000003 │ fkRGN8nY4pkE │ 1 │ >
│ 14 │ Customer#000000014 │ h3GFMzeFfYiamqr │ 1 │ >
│ 30 │ Customer#000000030 │ EhnzmgkqQw7UXhF0PVdg gLfSAihaaHaD2fZah2 │ 1 │ >
│ 59 │ Customer#000000059 │ tfcob0wJRYdypIJLzBckGW │ 1 │ >
│ 106 │ Customer#000000106 │ vkocmr6H6dl │ 1 │ >
├───────────┴────────────────────┴─────────────────────────────── ──────────┴─────────────┴─>
│ 5 rows >
└──────────────────────────────────────────────────────────────────────────────────────────>
Unlike SQL views, which will be registered to the system catalog, named queries are available only in the current scope (e.g., the current wvlet shell session).
Saving Queries in .wv Files
If you want to reuse the query in other sessions or share it with others, you can save the query to a file with .wv extension:
from customer
where c_nationkey = 1
Queries in .wv files can be loaded in from operator:
-- Load the query written in my_query.wv file
from 'my_query.wv'
In the wvlet shell, .wv files will be loaded from the current directory. If you want to load files from other directories, use -w (working directory) option to specify the base directory.
For advanced users, you can define reusable data models, which can accept some input parameters. Wvlet will find data models defined in .wv files in the working directory. See Data Models for more details.