medusa is a jdbc-utilities library that is designed to reduce writing code pertaining to jdbc. No more closing of connection manually, no spawning your own
preparedStatements. This helps reduce bugs where connection is not closed and bugs where column number are wrong.All this in a lightweight library that leverages Kotlin's ability to write DSLs. Medusa is not an ORM, it is just a utilities library to help you.
- Minimal use of reflection magic
- DSL which results in easier usage
- Asynchronous Transactions support (using Kotlin's coroutines)
- Transaction Support
- Async Transaction
- DSL for setting of config
- Standard database operations (query, queryList, insert, exec)
-
TransactionResulttype
- Reduce API differentiation for operation that returns a key and no key. (0.0.2)
- Extend config to have support for databases that cannot generate keys (0.0.2)
- Database
Connectionpooling using HikariCP - Removed
TransactionResulttype - Updated to Kotlin 1.3 coroutines, dispatches on
Dispatcher.IOby default fortransactionAsync
- Batch processing
- Proper logger instead of
println - Compile time generation of kotlin models based on database schema
- Customizable
Connectionpool, apart from HikariCP - Compile time generation of frequently used SQL statements. Eg.
INSERT INTO USER (email, username, passwordhash) VALUES (?,?,?)
- Logo (why not, I can also design no kappa)
- Website (again, why not lmao)
- An actual fullstack example using Jetbrain's Ktor
- Some simple benchmark
repositories {
jcenter()
}
dependencies {
compile group: 'mysql', name: 'mysql-connector-java', version: '6.0.6' //depends on the driver you need
compile 'com.budinverse.utils:medusa:<latest version>'
}Setting up your DatabaseConfig via built-in DSL
fun main(args: Array<String>) {
dbConfig {
databaseUser = "root"
databasePassword = "12345"
databaseUrl = "jdbc:mysql://localhost/medusa_test?useLegacyDatetimeCode=false&serverTimezone=UTC"
driver = "com.mysql.cj.jdbc.Driver"
connectionPool = connectionPool {
minimumIdle = 10
maximumPoolSize = 15
addDataSourceProperty("cachePrepStmts", "true")
addDataSourceProperty("prepStmtCacheSize", "250")
addDataSourceProperty("prepStmtCacheSqlLimit", "2048")
}
}
}Assume that all examples has the following User class
data class User(val id: Int = 0,
val name: String,
val age: Int) {
constructor(resultSet: ResultSet) : this(
resultSet["id"],
resultSet["name"],
resultSet["age"]
)
}A single query
fun queryPerson(): Person {
lateinit var personRes: ExecResult.SingleResult<Person>
transaction {
personRes = query {
statement = "SELECT * FROM User WHERE name = ?"
values = arrayOf("zeon111")
type = ::Person
}
}
return personRes.transformed // User(id=18, name=Zeon111, age=20)
}
Querying list of objects
fun queryListPerson(): ArrayList<Person> {
lateinit var personList: ExecResult.ListResult<Person>
transaction {
personList = queryList {
statement = "SELECT * FROM person"
type = ::Person
}
}
return personList.transformedList // [User(id=18, name=Zeon111, age=20), User(id=19, name=Zeon222, age=20)]
} fun insertTest(person: Person) {
lateinit var ins: ExecResult.SingleResult<Int>
transaction {
ins = insert {
statement = DummyData.insert
values = arrayOf(person.name, person.age)
type = {
it[1]
}
}
}
println(ins.transformed) // Auto generated PK
} For deletion just change the statement
fun updateTest(person: Person) {
lateinit var execResult: ExecResult.SingleResult<Person>
transaction {
execResult = update {
statement = "UPDATE person SET name = ?, age = ? WHERE id = ?"
values = arrayOf(person.name, person.age, 1)
type = ::Person
}
}
}As of now, since medusa is still not 1.0 yet, performance is NOT a focus. The focus is to provide and ergonomic API. However if you looking for ballpark of how medusa performs, here they are kappa
Computer: Intel Core i7 3770k @ 4.3Ghz, 16GB @ 2000Mhz RAM, Samsung 850 EVO 500GB, Windows 10 Education, MySQL 8.0
Medusa: Minimum 10, Maximum 15 connections in pool, Coroutines dispatched on Dispatchers.IO from standard library
Insert (asynchronous): Still benchmarking
Query (asynchronous): Still benchmarking
Computer: Macbook Pro (13-inch 2017) Intel Core i5 2.3Ghz, 8GB @ 2133Mhz
Medusa: Minimum 10, Maximum 15 connections in pool, Coroutines dispatched on Dispatchers.IO from standard library
Insert (asynchronous): Still benchmarking
Query (asynchronous): Still benchmarking
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