Skip to content

Commit

Permalink
Merge pull request #39 from hasura/codedmart/type-rep
Browse files Browse the repository at this point in the history 
ndc-spec type representation
  • Loading branch information
@gneeri
gneeri authored Jan 23, 2025
2 parents fe771ad + 67126aa commit 6556883
Show file tree
Hide file tree
Showing 16 changed files with 1,212 additions and 315 deletions.
35 changes: 30 additions & 5 deletions ndc-app/src/main/kotlin/io/hasura/ndc/app/services/JDBCSchemaGenerator.kt
View file
Original file line number Diff line number Diff line change
Expand Up @@ -4,8 +4,6 @@ import io.hasura.ndc.app.interfaces.ISchemaGenerator
import io.hasura.ndc.common.ConnectorConfiguration
import io.hasura.ndc.common.*
import io.hasura.ndc.ir.*
import jakarta.enterprise.context.ApplicationScoped
import jakarta.enterprise.inject.Default

abstract class JDBCSchemaGenerator(
private val supportsMutations: Boolean = false
Expand All @@ -15,6 +13,7 @@ abstract class JDBCSchemaGenerator(

abstract fun mapScalarType(
columnTypeStr: String,
numericPrecision: Int?,
numericScale: Int?
): NDCScalar

Expand Down Expand Up @@ -52,8 +51,8 @@ abstract class JDBCSchemaGenerator(
description = it.description,
arguments = emptyMap(),
type = when (it.nullable) {
true -> Type.Nullable(Type.Named(mapScalarType(it.type, it.numeric_scale).name))
false -> Type.Named(mapScalarType(it.type, it.numeric_scale).name)
true -> Type.Nullable(Type.Named(mapScalarType(it.type, it.numeric_precision, it.numeric_scale).name))
false -> Type.Named(mapScalarType(it.type, it.numeric_precision, it.numeric_scale).name)
}
)
}
Expand Down Expand Up @@ -87,7 +86,7 @@ abstract class JDBCSchemaGenerator(
name = function.function_name,
description = function.comment,
arguments = emptyMap(),
result_type = Type.Named(mapScalarType(function.data_type, null).name)
result_type = Type.Named(mapScalarType(function.data_type, null, null).name)
)
}

Expand All @@ -111,4 +110,30 @@ abstract class JDBCSchemaGenerator(
override fun getSchema(config: ConnectorConfiguration): SchemaResponse {
return buildSchema(config.tables, config.functions, config.nativeQueries)
}

fun mapNumericPrecisionAndScaleToNDCScalar(
precision: Int,
scale: Int
): NDCScalar {
return when {
scale != 0 -> when {
// FLOAT32: Up to 7 digits (values from -3.4028235E+38 to 3.4028235E+38).
precision <= 7 -> NDCScalar.FLOAT32
// FLOAT64: Up to 15 digits (values from -1.7976931348623157E+308 to 1.7976931348623157E+308).
precision <= 15 -> NDCScalar.FLOAT64
// BIGDECIMAL: More than 15 digits.
else -> NDCScalar.BIGDECIMAL
}
// INT8: Up to 3 digits (values from -128 to 127).
precision <= 3 -> NDCScalar.INT8
// INT16: Up to 5 digits (values from -32,768 to 32,767).
precision <= 5 -> NDCScalar.INT16
// INT32: Up to 10 digits (values from -2,147,483,648 to 2,147,483,647).
precision <= 10 -> NDCScalar.INT32
// INT64: Up to 19 digits (values from -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807).
precision <= 19 -> NDCScalar.INT64
// BIGINTEGER: More than 19 digits.
else -> NDCScalar.BIGINTEGER
}
}
}
3 changes: 2 additions & 1 deletion ndc-cli/src/main/kotlin/io/hasura/cli/MySQLConfigGenerator.kt
View file
Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@ object MySQLConfigGenerator : IConfigGenerator {

//language=MySQL
val sql = """
SELECT
SELECT
concat(tables.TABLE_SCHEMA, '.', tables.TABLE_NAME) AS TABLE_NAME,
tables.TABLE_TYPE,
tables.table_COMMENT as DESCRIPTION,
Expand All @@ -45,6 +45,7 @@ object MySQLConfigGenerator : IConfigGenerator {
'name', columns.column_name,
'description', columns.column_comment,
'type', columns.data_type,
'numeric_precision', columns.numeric_precision,
'numeric_scale', columns.numeric_scale,
'nullable', if (columns.is_nullable = 'yes', true, false),
'auto_increment', if(columns.extra = 'auto_increment',true,false),
Expand Down
1 change: 1 addition & 0 deletions ndc-cli/src/main/kotlin/io/hasura/cli/OracleConfigGenerator.kt
View file
Original file line number Diff line number Diff line change
Expand Up @@ -72,6 +72,7 @@ object OracleConfigGenerator : IConfigGenerator {
'description' VALUE column_comments.COMMENTS,
'type' VALUE columns.DATA_TYPE,
'numeric_scale' VALUE columns.DATA_SCALE,
'numeric_precision' VALUE columns.DATA_PRECISION,
'nullable' VALUE case when columns.NULLABLE = 'Y' then 'true' else 'false' end,
'auto_increment' VALUE case when columns.IDENTITY_COLUMN = 'YES' then 'true' else 'false' end
)
Expand Down
1 change: 1 addition & 0 deletions ndc-cli/src/main/kotlin/io/hasura/cli/SnowflakeConfigGenerator.kt
View file
Original file line number Diff line number Diff line change
Expand Up @@ -64,6 +64,7 @@ object SnowflakeConfigGenerator : IConfigGenerator {
'name', columns.column_name,
'description', columns.comment,
'type', columns.data_type,
'numeric_precision', columns.numeric_precision,
'numeric_scale', columns.numeric_scale,
'nullable', to_boolean(columns.is_nullable),
'auto_increment', to_boolean(columns.is_identity)
Expand Down
27 changes: 26 additions & 1 deletion ndc-cli/src/main/kotlin/io/hasura/cli/TrinoConfigGenerator.kt
View file
Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,24 @@ object TrinoConfigGenerator : IConfigGenerator {
WHERE table_schema = current_schema
""".trimIndent()


// Take a string of the format "decimal(20)" or "decimal(20,2)" and extract the numeric precision and scale
fun extractNumericPrecisionAndScale(
decimalString: String
): Pair<Int, Int> {
val (precision, scale) = decimalString
.substringAfter("(")
.substringBefore(")")
.let {
when {
it.contains(",") -> it.split(",")
else -> listOf(it, "0")
}
}
.map { it.toInt() }
return precision to scale
}

// fetch every column, use jOOQ's fetchGroups to group them by table_name
val tables = ctx.resultQuery(sql).fetchGroups("table_name").map { (tableName, rows) ->
TableSchemaRow(
Expand All @@ -38,19 +56,26 @@ object TrinoConfigGenerator : IConfigGenerator {
pks = emptyList(),
fks = emptyMap(),
columns = rows.map { row ->
val dataType = row.get("data_type", String::class.java)
val (numericPrecision, numericScale) = when {
dataType.startsWith("decimal") -> extractNumericPrecisionAndScale(dataType)
else -> null to null
}
ColumnSchemaRow(
name = row.get("column_name", String::class.java),
type = row.get("data_type", String::class.java),
nullable = row.get("is_nullable", String::class.java) == "YES",
auto_increment = false,
is_primarykey = false,
description = null,
numeric_scale = null
numeric_precision = numericPrecision,
numeric_scale = numericScale
)
},
)
}


return ConnectorConfiguration(
jdbcUrl = jdbcUrl,
jdbcProperties = emptyMap(),
Expand Down
38 changes: 9 additions & 29 deletions ndc-connector-mysql/src/main/kotlin/io/hasura/mysql/JSONGenerator.kt
View file
Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@ import io.hasura.ndc.common.NDCScalar
import io.hasura.ndc.ir.*
import io.hasura.ndc.ir.Field.ColumnField
import io.hasura.ndc.ir.Field as IRField
import io.hasura.ndc.ir.Type
import io.hasura.ndc.sqlgen.BaseQueryGenerator
import org.jooq.*
import org.jooq.Field
Expand Down Expand Up @@ -123,12 +124,16 @@ object JsonQueryGenerator : BaseQueryGenerator() {
(request.query.fields ?: emptyMap()).map { (alias, field) ->
when (field) {
is ColumnField -> {
val columnField = DSL.field(DSL.name(field.column))
val (columnType, ndcScalar) = columnTypeTojOOQType(
MySQLJDBCSchemaGenerator::mapScalarType,
request.collection,
field
)
val castedField = castToSQLDataType(MYSQL, columnField, ndcScalar)
DSL.jsonEntry(
alias,
DSL.field(
DSL.name(field.column),
// columnTypeTojOOQType(request.collection, field)
)
castedField
)
}

Expand Down Expand Up @@ -230,31 +235,6 @@ object JsonQueryGenerator : BaseQueryGenerator() {
}
}

private fun ndcScalarTypeToSQLDataType(scalarType: NDCScalar): DataType<out Any> = when (scalarType) {
NDCScalar.BOOLEAN -> SQLDataType.BOOLEAN
NDCScalar.INT -> SQLDataType.INTEGER
NDCScalar.FLOAT -> SQLDataType.FLOAT
NDCScalar.STRING -> SQLDataType.CLOB
NDCScalar.DATE -> SQLDataType.DATE
NDCScalar.DATETIME -> SQLDataType.TIMESTAMP
NDCScalar.DATETIME_WITH_TIMEZONE -> SQLDataType.TIMESTAMP
NDCScalar.TIME -> SQLDataType.TIME
NDCScalar.TIME_WITH_TIMEZONE -> SQLDataType.TIME
}

private fun columnTypeTojOOQType(collection: String, field: ColumnField): org.jooq.DataType<out Any> {
val connectorConfig = ConnectorConfiguration.Loader.config

val table = connectorConfig.tables.find { it.tableName == collection }
?: error("Table $collection not found in connector configuration")

val column = table.columns.find { it.name == field.column }
?: error("Column ${field.column} not found in table $collection")

val scalarType = MySQLJDBCSchemaGenerator.mapScalarType(column.type, column.numeric_scale)
return ndcScalarTypeToSQLDataType(scalarType)
}

private fun getAggregatejOOQFunction(aggregate: Aggregate) = when (aggregate) {
is Aggregate.StarCount -> DSL.count()
is Aggregate.SingleColumn -> {
Expand Down
Loading

0 comments on commit 6556883

Please sign in to comment.