AWS AppSync JavaScript resolver function reference for Amazon RDS

The select utility creates a SELECT statement to query your relational database.

Basic use

In its basic form, you can specify the table you want to query:

import { select, createPgStatement } from '@aws-appsync/utils/rds';

export function request(ctx) {

    // Generates statement: 
    // "SELECT * FROM "persons"
    return createPgStatement(select({table: 'persons'}));
}

Note that you can also specify the schema in your table identifier:

import { select, createPgStatement } from '@aws-appsync/utils/rds';

export function request(ctx) {

    // Generates statement:
    // SELECT * FROM "private"."persons"
    return createPgStatement(select({table: 'private.persons'}));
}

Specifying columns

You can specify columns with the columns property. If this isn't set to a value, it defaults to *:

export function request(ctx) {

    // Generates statement:
    // SELECT "id", "name"
    // FROM "persons"
    return createPgStatement(select({
        table: 'persons',
        columns: ['id', 'name']
    }));
}

You can specify a column's table as well:

export function request(ctx) {

    // Generates statement: 
    // SELECT "id", "persons"."name"
    // FROM "persons"
    return createPgStatement(select({
        table: 'persons',
        columns: ['id', 'persons.name']
    }));
}

Limits and offsets

You can apply limit and offset to the query:

export function request(ctx) {

    // Generates statement: 
    // SELECT "id", "name"
    // FROM "persons"
    // LIMIT :limit
    // OFFSET :offset
    return createPgStatement(select({
        table: 'persons',
        columns: ['id', 'name'],
        limit: 10,
        offset: 40
    }));
}

Order By

You can sort your results with the orderBy property. Provide an array of objects specifying the column and an optional dir property:

export function request(ctx) {

    // Generates statement: 
    // SELECT "id", "name" FROM "persons"
    // ORDER BY "name", "id" DESC
    return createPgStatement(select({
        table: 'persons',
        columns: ['id', 'name'],
        orderBy: [{column: 'name'}, {column: 'id', dir: 'DESC'}]
    }));
}

Filters

You can build filters by using the special condition object:

export function request(ctx) {

    // Generates statement:
    // SELECT "id", "name"
    // FROM "persons"
    // WHERE "name" = :NAME
    return createPgStatement(select({
        table: 'persons',
        columns: ['id', 'name'],
        where: {name: {eq: 'Stephane'}}
    }));
}

You can also combine filters:

export function request(ctx) {

    // Generates statement:
    // SELECT "id", "name"
    // FROM "persons"
    // WHERE "name" = :NAME and "id" > :ID
    return createPgStatement(select({
        table: 'persons',
        columns: ['id', 'name'],
        where: {name: {eq: 'Stephane'}, id: {gt: 10}}
    }));
}

You can also create OR statements:

export function request(ctx) {

    // Generates statement:
    // SELECT "id", "name"
    // FROM "persons"
    // WHERE "name" = :NAME OR "id" > :ID
    return createPgStatement(select({
        table: 'persons',
        columns: ['id', 'name'],
        where: { or: [
            { name: { eq: 'Stephane'} },
            { id: { gt: 10 } }
        ]}
    }));
}

You can also negate a condition with not:

export function request(ctx) {

    // Generates statement:
    // SELECT "id", "name"
    // FROM "persons"
    // WHERE NOT ("name" = :NAME AND "id" > :ID)
    return createPgStatement(select({
        table: 'persons',
        columns: ['id', 'name'],
        where: { not: [
            { name: { eq: 'Stephane'} },
            { id: { gt: 10 } }
        ]}
    }));
}

You can also use the following operators to compare values:

The insert utility provides a straightforward way of inserting single row items in your database with the INSERT operation.

Single item insertions

To insert an item, specify the table and then pass in your object of values. The object keys are mapped to your table columns. Columns names are automatically escaped, and values are sent to the database using the variable map:

import { insert, createMySQLStatement } from '@aws-appsync/utils/rds';

export function request(ctx) {
    const { input: values } = ctx.args;
    const insertStatement = insert({ table: 'persons', values });
    
    // Generates statement:
    // INSERT INTO `persons`(`name`)
    // VALUES(:NAME)
    return createMySQLStatement(insertStatement)
}

MySQL use case

You can combine an insert followed by a select to retrieve your inserted row:

import { insert, select, createMySQLStatement } from '@aws-appsync/utils/rds';

export function request(ctx) {
    const { input: values } = ctx.args;
    const insertStatement = insert({  table: 'persons', values });
    const selectStatement = select({
        table: 'persons',
        columns: '*',
        where: { id: { eq: values.id } },
        limit: 1,
    });
    
    // Generates statement:
    // INSERT INTO `persons`(`name`)
    // VALUES(:NAME)
    // and
    // SELECT *
    // FROM `persons`
    // WHERE `id` = :ID
    return createMySQLStatement(insertStatement, selectStatement)
}

Postgres use case

With Postgres, you can use returning to obtain data from the row that you inserted. It accepts * or an array of column names:

import { insert, createPgStatement } from '@aws-appsync/utils/rds';

export function request(ctx) {
    const { input: values } = ctx.args;
    const insertStatement = insert({
        table: 'persons',
        values,
        returning: '*'
    });

    // Generates statement:
    // INSERT INTO "persons"("name")
    // VALUES(:NAME)
    // RETURNING *
    return createPgStatement(insertStatement)
}

The update utility allows you to update existing rows. You can use the condition object to apply changes to the specified columns in all the rows that satisfy the condition. For example, let's say we have a schema that allows us to make this mutation. We want to update the name of Person with the id value of 3 but only if we've known them (known_since) since the year 2000:

mutation Update {
    updatePerson(
        input: {id: 3, name: "Jon"},
        condition: {known_since: {ge: "2000"}}
    ) {
    id
    name
  }
}

Our update resolver looks like this:

import { update, createPgStatement } from '@aws-appsync/utils/rds';

export function request(ctx) {
    const { input: { id, ...values }, condition } = ctx.args;
    const where = {
        ...condition,
        id: { eq: id },
    };
    const updateStatement = update({
        table: 'persons',
        values,
        where,
        returning: ['id', 'name'],
    });

    // Generates statement:
    // UPDATE "persons"
    // SET "name" = :NAME, "birthday" = :BDAY, "country" = :COUNTRY
    // WHERE "id" = :ID
    // RETURNING "id", "name"
    return createPgStatement(updateStatement)
}

We can add a check to our condition to make sure that only the row that has the primary key id equal to 3 is updated. Similarly, for Postgres inserts, you can use returning to return the modified data.

The remove utility allows you to delete existing rows. You can use the condition object on all rows that satisfy the condition. Note that delete is a reserved keyword in JavaScript. remove should be used instead:

import { remove, createPgStatement } from '@aws-appsync/utils/rds';

export function request(ctx) {
    const { input: { id }, condition } = ctx.args;
    const where = { ...condition, id: { eq: id } };
    const deleteStatement = remove({
        table: 'persons',
        where,
        returning: ['id', 'name'],
    });

    // Generates statement:
    // DELETE "persons"
    // WHERE "id" = :ID
    // RETURNING "id", "name"
    return createPgStatement(updateStatement)
}