Query Lanjutan
Di Gorm, Anda bisa secara efektif untuk memilih field menggunakan metode Select
. Hal ini sangat berguna ketika Anda memiliki model data yang besar, tetapi hanya membutuhkan sebagian kecil dari field tersebut, terutama saat mengirimkan API response.
type User struct { |
NOTE In
QueryFields
mode, all model fields are selected by their names.
db, err := gorm.Open(sqlite.Open("gorm.db"), &gorm.Config{ |
Locking
GORM mendukung berbagai jenis penguncian, misalnya:
// Basic FOR UPDATE lock |
The above statement will lock the selected rows for the duration of the transaction. This can be used in scenarios where you are preparing to update the rows and want to prevent other transactions from modifying them until your transaction is complete.
The Strength
can be also set to SHARE
which locks the rows in a way that allows other transactions to read the locked rows but not to update or delete them.
db.Clauses(clause.Locking{ |
The Table
option can be used to specify the table to lock. This is useful when you are joining multiple tables and want to lock only one of them.
Options can be provided like NOWAIT
which tries to acquire a lock and fails immediately with an error if the lock is not available. It prevents the transaction from waiting for other transactions to release their locks.
db.Clauses(clause.Locking{ |
Another option can be SKIP LOCKED
which skips over any rows that are already locked by other transactions. This is useful in high concurrency situations where you want to process rows that are not currently locked by other transactions.
For more advanced locking strategies, refer to Raw SQL and SQL Builder.
Sub-Kueri
Subqueries are a powerful feature in SQL, allowing nested queries. GORM can generate subqueries automatically when using a *gorm.DB object as a parameter.
// Simple subquery |
Dari Sub-Kueri
GORM allows the use of subqueries in the FROM clause, enabling complex queries and data organization.
// Using subquery in FROM clause |
Pengelompokan Kondisi
Group Conditions in GORM provide a more readable and maintainable way to write complex SQL queries involving multiple conditions.
// Complex SQL query using Group Conditions |
IN dengan Beberapa Kolom
GORM supports the IN clause with multiple columns, allowing you to filter data based on multiple field values in a single query.
// Using IN with multiple columns |
Argumen Bernama
GORM enhances the readability and maintainability of SQL queries by supporting named arguments. This feature allows for clearer and more organized query construction, especially in complex queries with multiple parameters. Named arguments can be utilized using either sql.NamedArg
or map[string]interface{}{}
, providing flexibility in how you structure your queries.
// Example using sql.NamedArg for named arguments |
For more examples and details, see Raw SQL and SQL Builder
Pencarian ke Map
GORM provides flexibility in querying data by allowing results to be scanned into a map[string]interface{}
or []map[string]interface{}
, which can be useful for dynamic data structures.
When using Find To Map
, it’s crucial to include Model
or Table
in your query to explicitly specify the table name. This ensures that GORM understands which table to query against.
// Scanning the first result into a map with Model |
FirstOrInit
GORM’s FirstOrInit
method is utilized to fetch the first record that matches given conditions, or initialize a new instance if no matching record is found. This method is compatible with both struct and map conditions and allows additional flexibility with the Attrs
and Assign
methods.
// If no User with the name "non_existing" is found, initialize a new User |
Using Attrs
for Initialization
When no record is found, you can use Attrs
to initialize a struct with additional attributes. These attributes are included in the new struct but are not used in the SQL query.
// If no User is found, initialize with given conditions and additional attributes |
Using Assign
for Attributes
The Assign
method allows you to set attributes on the struct regardless of whether the record is found or not. These attributes are set on the struct but are not used to build the SQL query and the final data won’t be saved into the database.
// Initialize with given conditions and Assign attributes, regardless of record existence |
FirstOrInit
, along with Attrs
and Assign
, provides a powerful and flexible way to ensure a record exists and is initialized or updated with specific attributes in a single step.
FirstOrCreate
FirstOrCreate
in GORM is used to fetch the first record that matches given conditions or create a new one if no matching record is found. This method is effective with both struct and map conditions. The RowsAffected
property is useful to determine the number of records created or updated.
// Create a new record if not found |
Using Attrs
with FirstOrCreate
Attrs
can be used to specify additional attributes for the new record if it is not found. These attributes are used for creation but not in the initial search query.
// Create a new record with additional attributes if not found |
Using Assign
with FirstOrCreate
The Assign
method sets attributes on the record regardless of whether it is found or not, and these attributes are saved back to the database.
// Initialize and save new record with `Assign` attributes if not found |
Optimizer/Indeks Hints
GORM includes support for optimizer and index hints, allowing you to influence the query optimizer’s execution plan. This can be particularly useful in optimizing query performance or when dealing with complex queries.
Optimizer hints are directives that suggest how a database’s query optimizer should execute a query. GORM facilitates the use of optimizer hints through the gorm.io/hints package.
import "gorm.io/hints" |
Index Hints
Index hints provide guidance to the database about which indexes to use. They can be beneficial if the query planner is not selecting the most efficient indexes for a query.
import "gorm.io/hints" |
These hints can significantly impact query performance and behavior, especially in large databases or complex data models. For more detailed information and additional examples, refer to Optimizer Hints/Index/Comment in the GORM documentation.
Pengulangan
GORM supports the iteration over query results using the Rows
method. This feature is particularly useful when you need to process large datasets or perform operations on each record individually.
You can iterate through rows returned by a query, scanning each row into a struct. This method provides granular control over how each record is handled.
rows, err := db.Model(&User{}).Where("name = ?", "jinzhu").Rows() |
This approach is ideal for complex data processing that cannot be easily achieved with standard query methods.
FindInBatches
FindInBatches
allows querying and processing records in batches. This is especially useful for handling large datasets efficiently, reducing memory usage and improving performance.
With FindInBatches
, GORM processes records in specified batch sizes. Inside the batch processing function, you can apply operations to each batch of records.
// Processing records in batches of 100 |
FindInBatches
is an effective tool for processing large volumes of data in manageable chunks, optimizing resource usage and performance.
Hook Kueri
GORM offers the ability to use hooks, such as AfterFind
, which are triggered during the lifecycle of a query. These hooks allow for custom logic to be executed at specific points, such as after a record has been retrieved from the database.
This hook is useful for post-query data manipulation or default value settings. For more detailed information and additional hook types, refer to Hooks in the GORM documentation.
func (u *User) AfterFind(tx *gorm.DB) (err error) { |
Pluck
The Pluck
method in GORM is used to query a single column from the database and scan the result into a slice. This method is ideal for when you need to retrieve specific fields from a model.
If you need to query more than one column, you can use Select
with Scan or Find instead.
// Retrieving ages of all users |
Scopes
Scopes
in GORM are a powerful feature that allows you to define commonly-used query conditions as reusable methods. These scopes can be easily referenced in your queries, making your code more modular and readable.
Defining Scopes
Scopes
are defined as functions that modify and return a gorm.DB
instance. You can define a variety of conditions as scopes based on your application’s requirements.
// Scope for filtering records where amount is greater than 1000 |
Applying Scopes in Queries
You can apply one or more scopes to a query by using the Scopes
method. This allows you to chain multiple conditions dynamically.
// Applying scopes to find all credit card orders with an amount greater than 1000 |
Scopes
are a clean and efficient way to encapsulate common query logic, enhancing the maintainability and readability of your code. For more detailed examples and usage, refer to Scopes in the GORM documentation.
Count
The Count
method in GORM is used to retrieve the number of records that match a given query. It’s a useful feature for understanding the size of a dataset, particularly in scenarios involving conditional queries or data analysis.
Getting the Count of Matched Records
You can use Count
to determine the number of records that meet specific criteria in your queries.
var count int64 |
Count with Distinct and Group
GORM also allows counting distinct values and grouping results.
// Counting distinct names |