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Version: 2.0.x

Deep dive

Inserts in depth

Table description

As usual, in order to use the DSL, first thing we need to do is to create meta-model of our table. Let’s imagine we have a customers table in postgres (in case of a different database just extend the appropriate module) To describe table, create a simple case class which describes table data. Derive implicit Schema for that type and just call defineTable with the type parameter of that case class. To extract columns from table call columns method on your table, which returns a flat tuple of all columns.

import zio.sql.postgresql.PostgresJdbcModule

trait TableModel extends PostgresJdbcModule {

case class Customer(id: UUID, dob: LocalDate, firstName: String, lastName: String, verified: Boolean, createdTimestampString: String, createdTimestamp: ZonedDateTime)

implicit val custommerSchema = DeriveSchema.gen[Customer]

val customers = defineTable[Customer]

val (customerId, dob, fName, lName, verified, createdString, createdTimestamp) =
customers.columns
}

Then, to use zio-sql ’s inserts, just mix in TableModel trait from above, to your repository.

In case you’re wondering what those extracted columns are (customerId, dob etc), they are of a type called Expr. Expr[F, A, B] is fundamental abstraction in zio-sql which basically represents description of any SQL expression of type B, having a source of type A and a phantom type F. To give specific example, type of fName is

Expr[Features.Source[String(“first_name”)], customers.TableType, String]. 

This gives DSL huge power to remember table from which the column comes from, type of the columns and what kind of Expr we are dealing with. Don’t worry, you don’t need to remember any of this, but from now on we will use those Expr instances in our inserts.

In general, DSL is giving us two options how to approach inserts. We can insert either tuple values or used defined case class - which requires zio-schema instance (more on that later). Also your custom data type or tuple need to consist only of the types for which there is a TypeTag instance defined. Each sql module has a finite set of such types - those are the types that particular module can work with. In other words, types inside your tuples or case class need to correspond with the types of the extracted Exprs.

Insert tuples

Let’s say we want to build the query like the following one:

insert into 
customers(id, date_of_birth, first_name, last_name, verified_customer, created)
values
('60b01fc9-c902-4468-8d49-3c0f989def37',1983-01-05, 'Ronald', 'Russell', true, '2020-11-21 19:10:25+00')

zio-sql gives us nice typesafe DSL that feels similar to writing SQL:

insertInto(customers)
(customerId, dob, fName, lName, verified, created)
.values((UUID.randomUUID(), LocalDate.ofYearDay(1990, 1), "Ronald", "Russell", true, ZonedDateTime.now()))

Compiler verifies your inserts and your query fails with compile-time error at any of the following situations:

  • you mess up the order of values - e.g. you put Boolean where String is expected
  • you don’t specify all the not null columns of the table
  • you try to insert to columns from another table

Some details about syntax: insertInto method takes two value parameters. One is our table customers that we created before in Table description section. The other is an HList like collection of Expr’s, called Selection. You create it by appending Exprs with “++” operator. values method takes a Tuple6 of type (UUID, LocalDate, String, String, Boolean, ZonedDateTime). The required tuple is dependent on combination of Exprs. Just like with normal sql insert, you could swap fName with dob Expr and corresponding values and your query will work just fine. Compiler will only let you build such queries that won’t explode in runtime (in case you described your table correctly of course ! )

If we need to insert multiple values at once, all we need to do is to create any Seq of tuples and stick it into the overloaded values method.

val data =
List(
(UUID.randomUUID(), LocalDate.ofYearDay(1990, 1), "Ronald1", "Russel1", true, ZonedDateTime.now()),
(UUID.randomUUID(), LocalDate.ofYearDay(1980, 1), "Ronald2", "Russel2", false, ZonedDateTime.now()),
(UUID.randomUUID(), LocalDate.ofYearDay(1970, 1), "Ronald3", "Russel3", true, ZonedDateTime.now())
)

val query = insertInto(customers)(
customerId, dob, fName, lName, verified, createdString, createdTimestamp
).values(data)

In this case, data is of type List[(UUID, LocalDate, String, String, Boolean, ZonedDateTime)]

Insert custom case class

ZIO SQL lets you insert also your own case classes. Let’s define a customer case class:

final case class Customer(
id: UUID,
dateOfBirth: LocalDate,
firstName: String,
lastName: String,
verified: Boolean,
createdTimestamp: ZonedDateTime
)

In this case, the name of the fields makes no difference. Similarly to writing sql, the order of the fields is important.

zio-sql also needs an implicit instance of zio-schema for your data type. You can define it easily:

import zio.schema.DeriveSchema
implicit val customerSchema = DeriveSchema.gen[Customer]

Then your insert looks almost the same as before:

val data: Customer = Customer(UUID.randomUUID(), LocalDate.ofYearDay(1990, 1), "Ronald", "Russel", true, ZonedDateTime.now())

val query = insertInto(customers)(
customerId, dob, fName, lName, verified, createdString, createdTimestamp
).values(data)

Or you can insert multiple rows at once. Just define data as a List or any collection of your choice.

val data : List[Customer] = ???

Show generated SQL query

In case you want to see the exact query that zio-sql generated, you can use renderInsert method inside repo that has PostgresModule (or TableModel from above example) mixed in.

val query = insertInto(customers)(
customerId, dob, fName, lName, verified, createdString, createdTimestamp
).values((UUID.randomUUID(), LocalDate.ofYearDay(1990, 1), "Ronald", "Russell", true, ZonedDateTime.now()))

val sqlString: String = renderInsert(query)

Execute the query

In order to execute a query, we use execute method inside repo that has PostgresModule (or TableModel from the above example) mixed in.

val query = insertInto(customers)(
customerId, dob, fName, lName, verified, createdString, createdTimestamp
).values((UUID.randomUUID(), LocalDate.ofYearDay(1990, 1), "Ronald", "Russell", true, ZonedDateTime.now()))

val executed : ZIO[Has[SqlDriver], Exception, Int] = execute(query)

As the type of executed indicates, you need to provide an SqlDriver in order to run this effect. The result Int is the number of rows updated.

More examples

More examples can be found in zio-sql test suite (PostgresModuleSpec, SqlServerModuleSpec, …) or in zio-sql-example application in resources.

What is missing

As of now - Q1 2022 - zio-sql contributors is actively working on:

  • returning generated IDs from inserts
  • introduce nullable columns - for which user won’t need to input values
  • introduce auto generated columns - for which user cannot input values

Subqueries & Correlated subqueries

The goal of ZIO SQL is to give users the ability to describe also queries much more complex than just simple selects or joins. In this section we will introduce a few examples of subqueries and correlated subqueries. In case you will find a query which is not possible to write with zio-sql - or the generated sql query looks differently then expected - please contact us on discord and we will try to add your use case to the next release :) Now let’s explore what is possible today.

Subquery

Subquery is a query which is a part of another query. It’s executed first - before outer query - and then its result is used in outer query.

Now let’s say we want to build following query (this is on MSSQL Server) :

select order_id, product_id, unit_price 
from order_details
where unit_price > (select AVG(price) from product_prices )

We want to match details about orders, but we are interested only in those orders where price is higher than average price of all the products from product_prices table.

This is the meta model that we are working with:

case class ProductPrices(productId: UUID, effective: OffsetDateTime, price: BigDecimal)
case class OrderDetails(orderId: UUID, productId: UUID, unitPrice: BigDecimal)

implicit val productPricesSchema = DeriveSchema.gen[ProductPrices]
implicit val orderDetailsSchema = DeriveSchema.gen[OrderDetails]

val productPrices = defineTable[ProductPrices]
val (fkProductId, effective, price) = productPrices.columns

val orderDetails = defineTable[OrderDetails]
val (orderDetailsId, productId, unitPrice) = orderDetails.columns

We can create query very easily. In fact, just type it like a regular sql query and let your IDE auto completion guide you!

val query = select(orderDetailsId, productId, unitPrice)
.from(orderDetails)
.where(
unitPrice > select(Avg(price)).from(productPrices)
)

Then you can either execute the query to selected types or inspect sql query represented as a String. You just need a custom data type (Row in our example) to encapsulate results of a selection.

case class Row(orderId: UUID, productId: UUID, unitPrice: BigDecimal)

val result: ZStream[Has[SqlDriver],Exception,Row] = execute(query.to[UUID, UUID, BigDecimal, Row](Row.apply))

val sqlQuery: String = renderRead(query)

Similarly you can use subqueries inside select clause.

Correlated subqueries

Correlated subqueries are the ones that are executed after the outer query. They can be dependent on the result of the outer query and therefore they are executed for each resulting row of the outer query.

Lets say we want to build the following query:

select first_name, last_name, 
( select count(orders.id) from orders where customers.id = orders.customer_id ) as "count"
from customers

This would return the count of orders for each customer.

Description of tables:

case class Customers(id: UUID, firstName: String, lastName: String)
case class Orders(id: UUID, customerId: UUID, orderDate: LocalDate)

implicit val customerSchema = DeriveSchema.gen[Customers]
implicit val orderSchema = DeriveSchema.gen[Orders]

val customers = defineTable[Customers]
val (customerId, fName, lName) = customers.columns

val orders = defineTable[Orders]
val (orderId, fkCustomerId, orderDate) = orders.columns

ZIO SQL query:

val subquery =
customers.subselect(Count(orderId)).from(orders).where(fkCustomerId === customerId)

val query = select(fName, lName, (subquery as "Count")).from(customers)

All of these examples and more can be found and run in zio-sql tests.

Correlated subquery in from clause & Derived tables

Just one last, a little more complex example before we wrap up this section, for which we would use the same customers and orders tables as before.

Imagine we want to write a query that selects all customers with the date of their last order. If you approach this problem with JOIN, you end up with one row of a customer with the newest order. In fact, this is a good example of correlated subquery inside from clause, where subquery needs to access customer_id of the outer query. For this type of problems postgres introduced LATERAL keyword and MSSQL Server have CROSS APPLY and OUTER APPLY.

select customers.id, customers.first_name, customers.last_name, derived.order_date
from customers,
lateral (
select orders.order_date
from orders
where customers.id = orders.customer_id
order by orders.order_date desc limit 1 ) derived order by derived.order_date desc

Now it’s starting to be a little more complicated. First we need to create a subselect which can access columns from another source table - customers in our case. Then we specify this source as a type parameter to subselect. In order to build the whole query we also need derived.order_date which is coming from derived table, so that we can extract that column. We create derivedTable by calling asTable(tableName: String) method on subselect.

 val derivedTable  = subselect[customers.TableType](orderDate)
.from(orders)
.limit(1)
.where(customerId === fkCustomerId)
.orderBy(Ordering.Desc(orderDate))
.asTable("derived")

val orderDateDerived :*: _ = derivedTable

Finally, we have all the ingredients we need to describe our query with zio-sql.

import PostgresSpecific.PostgresSpecificTable._

val query =
select(customerId, fName, lName, orderDateDerived)
.from(customers.lateral(derivedTable))
.orderBy(Ordering.Desc(orderDateDerived))

Learning Resources