cloud-fan commented on a change in pull request #29795:
URL: https://github.com/apache/spark/pull/29795#discussion_r493187951
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
##########
@@ -541,57 +541,105 @@ case class StringToMap(text: Expression, pairDelim:
Expression, keyValueDelim: E
}
/**
- * Adds/replaces field in struct by name.
+ * Represents an operation to be applied to the fields of a struct.
*/
-case class WithFields(
- structExpr: Expression,
- names: Seq[String],
- valExprs: Seq[Expression]) extends Unevaluable {
+trait StructFieldsOperation {
- assert(names.length == valExprs.length)
+ val resolver: Resolver = SQLConf.get.resolver
+
+ /**
+ * Returns an updated list of StructFields and Expressions that will
ultimately be used
+ * as the fields argument for [[StructType]] and as the children argument for
+ * [[CreateNamedStruct]] respectively inside of [[UpdateFields]].
+ */
+ def apply(values: Seq[(StructField, Expression)]): Seq[(StructField,
Expression)]
+}
+
+/**
+ * Add or replace a field by name.
+ *
+ * We extend [[Unevaluable]] here to ensure that [[UpdateFields]] can include
it as part of its
+ * children, and thereby enable the analyzer to resolve and transform valExpr
as necessary.
+ */
+case class WithField(name: String, valExpr: Expression)
+ extends Unevaluable with StructFieldsOperation {
+
+ override def apply(values: Seq[(StructField, Expression)]):
Seq[(StructField, Expression)] = {
+ val newFieldExpr = (StructField(name, valExpr.dataType, valExpr.nullable),
valExpr)
+ if (values.exists { case (field, _) => resolver(field.name, name) }) {
+ values.map {
+ case (field, _) if resolver(field.name, name) => newFieldExpr
+ case x => x
+ }
+ } else {
+ values :+ newFieldExpr
+ }
+ }
+
+ override def children: Seq[Expression] = valExpr :: Nil
+
+ override def dataType: DataType = throw new UnresolvedException(this,
"dataType")
Review comment:
This is not really unresolved. If we don't expect to reach here,
probably `IllegalStateException` is better.
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
##########
@@ -541,57 +541,105 @@ case class StringToMap(text: Expression, pairDelim:
Expression, keyValueDelim: E
}
/**
- * Adds/replaces field in struct by name.
+ * Represents an operation to be applied to the fields of a struct.
*/
-case class WithFields(
- structExpr: Expression,
- names: Seq[String],
- valExprs: Seq[Expression]) extends Unevaluable {
+trait StructFieldsOperation {
- assert(names.length == valExprs.length)
+ val resolver: Resolver = SQLConf.get.resolver
+
+ /**
+ * Returns an updated list of StructFields and Expressions that will
ultimately be used
+ * as the fields argument for [[StructType]] and as the children argument for
+ * [[CreateNamedStruct]] respectively inside of [[UpdateFields]].
+ */
+ def apply(values: Seq[(StructField, Expression)]): Seq[(StructField,
Expression)]
+}
+
+/**
+ * Add or replace a field by name.
+ *
+ * We extend [[Unevaluable]] here to ensure that [[UpdateFields]] can include
it as part of its
+ * children, and thereby enable the analyzer to resolve and transform valExpr
as necessary.
+ */
+case class WithField(name: String, valExpr: Expression)
+ extends Unevaluable with StructFieldsOperation {
+
+ override def apply(values: Seq[(StructField, Expression)]):
Seq[(StructField, Expression)] = {
+ val newFieldExpr = (StructField(name, valExpr.dataType, valExpr.nullable),
valExpr)
+ if (values.exists { case (field, _) => resolver(field.name, name) }) {
Review comment:
nit: can we avoid iterating the `values` twice?
```
val result = ArrayBuffer.empty[(StructField, Expression)]
val newFieldExpr = ...
var hasMatch = false
for((field, expr) <- values) {
if (resolver(field.name, name)) {
hasMatch = true
...
} else ...
}
if (!hasMatch) result += newFieldExpr
result
```
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
##########
@@ -541,57 +541,105 @@ case class StringToMap(text: Expression, pairDelim:
Expression, keyValueDelim: E
}
/**
- * Adds/replaces field in struct by name.
+ * Represents an operation to be applied to the fields of a struct.
*/
-case class WithFields(
- structExpr: Expression,
- names: Seq[String],
- valExprs: Seq[Expression]) extends Unevaluable {
+trait StructFieldsOperation {
- assert(names.length == valExprs.length)
+ val resolver: Resolver = SQLConf.get.resolver
+
+ /**
+ * Returns an updated list of StructFields and Expressions that will
ultimately be used
+ * as the fields argument for [[StructType]] and as the children argument for
+ * [[CreateNamedStruct]] respectively inside of [[UpdateFields]].
+ */
+ def apply(values: Seq[(StructField, Expression)]): Seq[(StructField,
Expression)]
+}
+
+/**
+ * Add or replace a field by name.
+ *
+ * We extend [[Unevaluable]] here to ensure that [[UpdateFields]] can include
it as part of its
+ * children, and thereby enable the analyzer to resolve and transform valExpr
as necessary.
+ */
+case class WithField(name: String, valExpr: Expression)
+ extends Unevaluable with StructFieldsOperation {
+
+ override def apply(values: Seq[(StructField, Expression)]):
Seq[(StructField, Expression)] = {
+ val newFieldExpr = (StructField(name, valExpr.dataType, valExpr.nullable),
valExpr)
+ if (values.exists { case (field, _) => resolver(field.name, name) }) {
Review comment:
nit: can we avoid iterating the `values` twice?
```
val result = ArrayBuffer.empty[(StructField, Expression)]
val newFieldExpr = ...
var hasMatch = false
for((field, expr) <- values) {
if (resolver(field.name, name)) {
hasMatch = true
...
} else ...
}
if (!hasMatch) result += newFieldExpr
result.toArray
```
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
##########
@@ -541,57 +541,105 @@ case class StringToMap(text: Expression, pairDelim:
Expression, keyValueDelim: E
}
/**
- * Adds/replaces field in struct by name.
+ * Represents an operation to be applied to the fields of a struct.
*/
-case class WithFields(
- structExpr: Expression,
- names: Seq[String],
- valExprs: Seq[Expression]) extends Unevaluable {
+trait StructFieldsOperation {
- assert(names.length == valExprs.length)
+ val resolver: Resolver = SQLConf.get.resolver
+
+ /**
+ * Returns an updated list of StructFields and Expressions that will
ultimately be used
+ * as the fields argument for [[StructType]] and as the children argument for
+ * [[CreateNamedStruct]] respectively inside of [[UpdateFields]].
+ */
+ def apply(values: Seq[(StructField, Expression)]): Seq[(StructField,
Expression)]
+}
+
+/**
+ * Add or replace a field by name.
+ *
+ * We extend [[Unevaluable]] here to ensure that [[UpdateFields]] can include
it as part of its
+ * children, and thereby enable the analyzer to resolve and transform valExpr
as necessary.
+ */
+case class WithField(name: String, valExpr: Expression)
+ extends Unevaluable with StructFieldsOperation {
+
+ override def apply(values: Seq[(StructField, Expression)]):
Seq[(StructField, Expression)] = {
+ val newFieldExpr = (StructField(name, valExpr.dataType, valExpr.nullable),
valExpr)
+ if (values.exists { case (field, _) => resolver(field.name, name) }) {
+ values.map {
+ case (field, _) if resolver(field.name, name) => newFieldExpr
+ case x => x
+ }
+ } else {
+ values :+ newFieldExpr
+ }
+ }
+
+ override def children: Seq[Expression] = valExpr :: Nil
+
+ override def dataType: DataType = throw new UnresolvedException(this,
"dataType")
+
+ override def nullable: Boolean = throw new UnresolvedException(this,
"nullable")
+
+ override def prettyName: String = "WithField"
+}
+
+/**
+ * Drop a field by name.
+ */
+case class DropField(name: String) extends StructFieldsOperation {
+ override def apply(values: Seq[(StructField, Expression)]):
Seq[(StructField, Expression)] =
+ values.filterNot { case (field, _) => resolver(field.name, name) }
+}
+
+/**
+ * Updates fields in a struct.
+ */
+case class UpdateFields(structExpr: Expression, fieldOps:
Seq[StructFieldsOperation])
+ extends Unevaluable {
override def checkInputDataTypes(): TypeCheckResult = {
- if (!structExpr.dataType.isInstanceOf[StructType]) {
- TypeCheckResult.TypeCheckFailure(
- "struct argument should be struct type, got: " +
structExpr.dataType.catalogString)
+ val dataType = structExpr.dataType
+ if (!dataType.isInstanceOf[StructType]) {
+ TypeCheckResult.TypeCheckFailure("struct argument should be struct type,
got: " +
+ dataType.catalogString)
+ } else if (newExprs.isEmpty) {
+ TypeCheckResult.TypeCheckFailure("cannot drop all fields in struct")
} else {
TypeCheckResult.TypeCheckSuccess
}
}
- override def children: Seq[Expression] = structExpr +: valExprs
+ override def children: Seq[Expression] = structExpr +: fieldOps.collect {
+ case e: Expression => e
+ }
- override def dataType: StructType =
evalExpr.dataType.asInstanceOf[StructType]
+ override def dataType: StructType = StructType(newFields)
override def nullable: Boolean = structExpr.nullable
- override def prettyName: String = "with_fields"
+ override def prettyName: String = "update_fields"
- lazy val evalExpr: Expression = {
- val existingExprs =
structExpr.dataType.asInstanceOf[StructType].fieldNames.zipWithIndex.map {
- case (name, i) => (name, GetStructField(KnownNotNull(structExpr),
i).asInstanceOf[Expression])
+ private lazy val existingFieldExprs: Seq[(StructField, Expression)] =
+ structExpr.dataType.asInstanceOf[StructType].fields.zipWithIndex.map {
+ case (field, i) => (field, GetStructField(structExpr, i))
}
- val addOrReplaceExprs = names.zip(valExprs)
-
- val resolver = SQLConf.get.resolver
- val newExprs = addOrReplaceExprs.foldLeft(existingExprs) {
- case (resultExprs, newExpr @ (newExprName, _)) =>
- if (resultExprs.exists(x => resolver(x._1, newExprName))) {
- resultExprs.map {
- case (name, _) if resolver(name, newExprName) => newExpr
- case x => x
- }
- } else {
- resultExprs :+ newExpr
- }
- }.flatMap { case (name, expr) => Seq(Literal(name), expr) }
+ private lazy val newFieldExprs: Seq[(StructField, Expression)] =
+ fieldOps.foldLeft(existingFieldExprs)((exprs, op) => op(exprs))
- val expr = CreateNamedStruct(newExprs)
- if (structExpr.nullable) {
- If(IsNull(structExpr), Literal(null, expr.dataType), expr)
- } else {
- expr
- }
+ private lazy val newFields: Seq[StructField] = newFieldExprs.map(_._1)
+
+ lazy val newExprs: Seq[Expression] = newFieldExprs.map(_._2)
+
+ private lazy val createNamedStructExpr =
CreateNamedStruct(newFieldExprs.flatMap {
+ case (field, expr) => Seq(Literal(field.name), expr)
+ })
+
+ lazy val evalExpr: Expression = if (structExpr.nullable) {
Review comment:
nit: use local variable if possible
```
lazy val evalExpr: Expression = {
val createNamedStructExpr = ...
if (structExpr.nullable) ...
}
```
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/Column.scala
##########
@@ -901,39 +901,125 @@ class Column(val expr: Expression) extends Logging {
* // result: org.apache.spark.sql.AnalysisException: Ambiguous reference
to fields
* }}}
*
+ * This method supports adding/replacing nested fields directly e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".withField("a.c", lit(3)).withField("a.d",
lit(4)))
+ * // result: {"a":{"a":1,"b":2,"c":3,"d":4}}
+ * }}}
+ *
+ * However, if you are going to add/replace multiple nested fields, it is
more optimal to extract
+ * out the nested struct before adding/replacing multiple fields e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".withField("a", $"struct_col.a".withField("c",
lit(3)).withField("d", lit(4))))
+ * // result: {"a":{"a":1,"b":2,"c":3,"d":4}}
+ * }}}
+ *
* @group expr_ops
* @since 3.1.0
*/
// scalastyle:on line.size.limit
def withField(fieldName: String, col: Column): Column = withExpr {
require(fieldName != null, "fieldName cannot be null")
require(col != null, "col cannot be null")
+ updateFieldsHelper(expr, nameParts(fieldName), name => WithField(name,
col.expr))
+ }
- val nameParts = if (fieldName.isEmpty) {
+ // scalastyle:off line.size.limit
+ /**
+ * An expression that drops fields in `StructType` by name.
Review comment:
Let's explicitly mention that, if the name doesn't match any field, it's
noop.
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/Column.scala
##########
@@ -901,39 +901,125 @@ class Column(val expr: Expression) extends Logging {
* // result: org.apache.spark.sql.AnalysisException: Ambiguous reference
to fields
* }}}
*
+ * This method supports adding/replacing nested fields directly e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".withField("a.c", lit(3)).withField("a.d",
lit(4)))
+ * // result: {"a":{"a":1,"b":2,"c":3,"d":4}}
+ * }}}
+ *
+ * However, if you are going to add/replace multiple nested fields, it is
more optimal to extract
+ * out the nested struct before adding/replacing multiple fields e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".withField("a", $"struct_col.a".withField("c",
lit(3)).withField("d", lit(4))))
+ * // result: {"a":{"a":1,"b":2,"c":3,"d":4}}
+ * }}}
+ *
* @group expr_ops
* @since 3.1.0
*/
// scalastyle:on line.size.limit
def withField(fieldName: String, col: Column): Column = withExpr {
require(fieldName != null, "fieldName cannot be null")
require(col != null, "col cannot be null")
+ updateFieldsHelper(expr, nameParts(fieldName), name => WithField(name,
col.expr))
+ }
- val nameParts = if (fieldName.isEmpty) {
+ // scalastyle:off line.size.limit
+ /**
+ * An expression that drops fields in `StructType` by name.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
+ * df.select($"struct_col".dropFields("b"))
+ * // result: {"a":1}
+ *
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
+ * df.select($"struct_col".dropFields("c"))
+ * // result: {"a":1,"b":2}
+ *
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2, 'c', 3) struct_col")
+ * df.select($"struct_col".dropFields("b", "c"))
+ * // result: {"a":1}
+ *
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
+ * df.select($"struct_col".dropFields("a", "b"))
+ * // result: org.apache.spark.sql.AnalysisException: cannot resolve
'update_fields(update_fields(`struct_col`))' due to data type mismatch: cannot
drop all fields in struct
+ *
+ * val df = sql("SELECT CAST(NULL AS struct<a:int,b:int>) struct_col")
+ * df.select($"struct_col".dropFields("b"))
+ * // result: null of type struct<a:int>
+ *
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2, 'b', 3) struct_col")
+ * df.select($"struct_col".dropFields("b"))
+ * // result: {"a":1}
+ *
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".dropFields("a.b"))
+ * // result: {"a":{"a":1}}
+ *
+ * val df = sql("SELECT named_struct('a', named_struct('b', 1), 'a',
named_struct('c', 2)) struct_col")
+ * df.select($"struct_col".dropFields("a.c"))
+ * // result: org.apache.spark.sql.AnalysisException: Ambiguous reference
to fields
+ * }}}
+ *
+ * This method supports dropping multiple nested fields directly e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".dropFields("a.b", "a.c"))
+ * // result: {"a":{"a":1}}
+ * }}}
+ *
+ * However, if you are going to drop multiple nested fields, it is more
optimal to extract
+ * out the nested struct before dropping multiple fields from it e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".withField("a", $"struct_col.a".dropFields("b",
"c")))
+ * // result: {"a":{"a":1}}
+ * }}}
+ *
+ * @group expr_ops
+ * @since 3.1.0
+ */
+ // scalastyle:on line.size.limit
+ def dropFields(fieldNames: String*): Column = withExpr {
+ def dropField(structExpr: Expression, fieldName: String): UpdateFields =
+ updateFieldsHelper(structExpr, nameParts(fieldName), name =>
DropField(name))
+
+ fieldNames.tail.foldLeft(dropField(expr, fieldNames.head)) {
+ (resExpr, fieldName) => dropField(resExpr, fieldName)
+ }
+ }
+
+ private def nameParts(fieldName: String): Seq[String] = {
+ require(fieldName != null, "fieldName cannot be null")
+
+ if (fieldName.isEmpty) {
fieldName :: Nil
Review comment:
shall we fail here? I don't think the field name can be an empty string.
It's not related to this PR and we can consider it later.
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/Column.scala
##########
@@ -901,39 +901,125 @@ class Column(val expr: Expression) extends Logging {
* // result: org.apache.spark.sql.AnalysisException: Ambiguous reference
to fields
* }}}
*
+ * This method supports adding/replacing nested fields directly e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".withField("a.c", lit(3)).withField("a.d",
lit(4)))
+ * // result: {"a":{"a":1,"b":2,"c":3,"d":4}}
+ * }}}
+ *
+ * However, if you are going to add/replace multiple nested fields, it is
more optimal to extract
+ * out the nested struct before adding/replacing multiple fields e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".withField("a", $"struct_col.a".withField("c",
lit(3)).withField("d", lit(4))))
+ * // result: {"a":{"a":1,"b":2,"c":3,"d":4}}
+ * }}}
+ *
* @group expr_ops
* @since 3.1.0
*/
// scalastyle:on line.size.limit
def withField(fieldName: String, col: Column): Column = withExpr {
require(fieldName != null, "fieldName cannot be null")
require(col != null, "col cannot be null")
+ updateFieldsHelper(expr, nameParts(fieldName), name => WithField(name,
col.expr))
+ }
- val nameParts = if (fieldName.isEmpty) {
+ // scalastyle:off line.size.limit
+ /**
+ * An expression that drops fields in `StructType` by name.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
+ * df.select($"struct_col".dropFields("b"))
+ * // result: {"a":1}
+ *
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
+ * df.select($"struct_col".dropFields("c"))
+ * // result: {"a":1,"b":2}
+ *
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2, 'c', 3) struct_col")
+ * df.select($"struct_col".dropFields("b", "c"))
+ * // result: {"a":1}
+ *
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
+ * df.select($"struct_col".dropFields("a", "b"))
+ * // result: org.apache.spark.sql.AnalysisException: cannot resolve
'update_fields(update_fields(`struct_col`))' due to data type mismatch: cannot
drop all fields in struct
+ *
+ * val df = sql("SELECT CAST(NULL AS struct<a:int,b:int>) struct_col")
+ * df.select($"struct_col".dropFields("b"))
+ * // result: null of type struct<a:int>
+ *
+ * val df = sql("SELECT named_struct('a', 1, 'b', 2, 'b', 3) struct_col")
+ * df.select($"struct_col".dropFields("b"))
+ * // result: {"a":1}
+ *
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".dropFields("a.b"))
+ * // result: {"a":{"a":1}}
+ *
+ * val df = sql("SELECT named_struct('a', named_struct('b', 1), 'a',
named_struct('c', 2)) struct_col")
+ * df.select($"struct_col".dropFields("a.c"))
+ * // result: org.apache.spark.sql.AnalysisException: Ambiguous reference
to fields
+ * }}}
+ *
+ * This method supports dropping multiple nested fields directly e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".dropFields("a.b", "a.c"))
+ * // result: {"a":{"a":1}}
+ * }}}
+ *
+ * However, if you are going to drop multiple nested fields, it is more
optimal to extract
+ * out the nested struct before dropping multiple fields from it e.g.
+ *
+ * {{{
+ * val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2))
struct_col")
+ * df.select($"struct_col".withField("a", $"struct_col.a".dropFields("b",
"c")))
+ * // result: {"a":{"a":1}}
+ * }}}
+ *
+ * @group expr_ops
+ * @since 3.1.0
+ */
+ // scalastyle:on line.size.limit
+ def dropFields(fieldNames: String*): Column = withExpr {
+ def dropField(structExpr: Expression, fieldName: String): UpdateFields =
+ updateFieldsHelper(structExpr, nameParts(fieldName), name =>
DropField(name))
+
+ fieldNames.tail.foldLeft(dropField(expr, fieldNames.head)) {
+ (resExpr, fieldName) => dropField(resExpr, fieldName)
+ }
+ }
+
+ private def nameParts(fieldName: String): Seq[String] = {
+ require(fieldName != null, "fieldName cannot be null")
+
+ if (fieldName.isEmpty) {
fieldName :: Nil
} else {
CatalystSqlParser.parseMultipartIdentifier(fieldName)
}
- withFieldHelper(expr, nameParts, Nil, col.expr)
}
- private def withFieldHelper(
- struct: Expression,
- namePartsRemaining: Seq[String],
- namePartsDone: Seq[String],
- value: Expression) : WithFields = {
- val name = namePartsRemaining.head
+ private def updateFieldsHelper(
+ structExpr: Expression,
Review comment:
nit: 4 space indentation.
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala
##########
@@ -159,6 +160,14 @@ abstract class QueryTest extends PlanTest {
checkAnswer(df, expectedAnswer.collect())
}
+ protected def checkAnswer(
+ df: => DataFrame,
+ expectedAnswer: Seq[Row],
Review comment:
nit: 4 space indentation.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
