How to select a subset of fields from an array column in Spark Java?

-1

This question is same as the one posted here. It has an accepted answer for scala. But I need to implement the same in Java.

How to select a subset of fields from an array column in Spark?

import org.apache.spark.sql.Row



case class Record(id: String, size: Int)



val dropUseless = udf((xs: Seq[Row]) =>  xs.map{

  case Row(id: String, size: Int, _) => Record(id, size)

})



df.select(dropUseless($"subClasss"))

I have tried to implement the above in java but couldn't get it working. Appreciate any help. Thanks

this.spark.udf().register("dropUseless",

            (UDF1<Seq<Row>, Seq<Row>>) rows -> {

                Seq<Row> seq = JavaConversions

                    .asScalaIterator(

                        JavaConversions.seqAsJavaList(rows)

                            .stream()

                            .map((Row t) -> RowFactory.create(new Object {t.getAs("id"), t.getAs("size")})

                            ).iterator())

                    .toSeq();

                return seq;

            }, DataTypes.createStructType(Arrays.asList(

                DataTypes.createStructField("id", DataTypes.StringType, false),

                DataTypes.createStructField("size", DataTypes.IntegerType, true))

                )

            );

edited Nov 24 '18 at 9:04

asked Nov 24 '18 at 8:59

gbgunz

add a comment |

-1

This question is same as the one posted here. It has an accepted answer for scala. But I need to implement the same in Java.

How to select a subset of fields from an array column in Spark?

import org.apache.spark.sql.Row



case class Record(id: String, size: Int)



val dropUseless = udf((xs: Seq[Row]) =>  xs.map{

  case Row(id: String, size: Int, _) => Record(id, size)

})



df.select(dropUseless($"subClasss"))

I have tried to implement the above in java but couldn't get it working. Appreciate any help. Thanks

this.spark.udf().register("dropUseless",

            (UDF1<Seq<Row>, Seq<Row>>) rows -> {

                Seq<Row> seq = JavaConversions

                    .asScalaIterator(

                        JavaConversions.seqAsJavaList(rows)

                            .stream()

                            .map((Row t) -> RowFactory.create(new Object {t.getAs("id"), t.getAs("size")})

                            ).iterator())

                    .toSeq();

                return seq;

            }, DataTypes.createStructType(Arrays.asList(

                DataTypes.createStructField("id", DataTypes.StringType, false),

                DataTypes.createStructField("size", DataTypes.IntegerType, true))

                )

            );

edited Nov 24 '18 at 9:04

asked Nov 24 '18 at 8:59

gbgunz

add a comment |

-1

This question is same as the one posted here. It has an accepted answer for scala. But I need to implement the same in Java.

How to select a subset of fields from an array column in Spark?

import org.apache.spark.sql.Row



case class Record(id: String, size: Int)



val dropUseless = udf((xs: Seq[Row]) =>  xs.map{

  case Row(id: String, size: Int, _) => Record(id, size)

})



df.select(dropUseless($"subClasss"))

I have tried to implement the above in java but couldn't get it working. Appreciate any help. Thanks

this.spark.udf().register("dropUseless",

            (UDF1<Seq<Row>, Seq<Row>>) rows -> {

                Seq<Row> seq = JavaConversions

                    .asScalaIterator(

                        JavaConversions.seqAsJavaList(rows)

                            .stream()

                            .map((Row t) -> RowFactory.create(new Object {t.getAs("id"), t.getAs("size")})

                            ).iterator())

                    .toSeq();

                return seq;

            }, DataTypes.createStructType(Arrays.asList(

                DataTypes.createStructField("id", DataTypes.StringType, false),

                DataTypes.createStructField("size", DataTypes.IntegerType, true))

                )

            );

edited Nov 24 '18 at 9:04

asked Nov 24 '18 at 8:59

gbgunz

This question is same as the one posted here. It has an accepted answer for scala. But I need to implement the same in Java.

How to select a subset of fields from an array column in Spark?

import org.apache.spark.sql.Row



case class Record(id: String, size: Int)



val dropUseless = udf((xs: Seq[Row]) =>  xs.map{

  case Row(id: String, size: Int, _) => Record(id, size)

})



df.select(dropUseless($"subClasss"))

I have tried to implement the above in java but couldn't get it working. Appreciate any help. Thanks

this.spark.udf().register("dropUseless",

            (UDF1<Seq<Row>, Seq<Row>>) rows -> {

                Seq<Row> seq = JavaConversions

                    .asScalaIterator(

                        JavaConversions.seqAsJavaList(rows)

                            .stream()

                            .map((Row t) -> RowFactory.create(new Object {t.getAs("id"), t.getAs("size")})

                            ).iterator())

                    .toSeq();

                return seq;

            }, DataTypes.createStructType(Arrays.asList(

                DataTypes.createStructField("id", DataTypes.StringType, false),

                DataTypes.createStructField("size", DataTypes.IntegerType, true))

                )

            );

java apache-spark-sql

edited Nov 24 '18 at 9:04

asked Nov 24 '18 at 8:59

gbgunz

edited Nov 24 '18 at 9:04

asked Nov 24 '18 at 8:59

gbgunz

edited Nov 24 '18 at 9:04

asked Nov 24 '18 at 8:59

gbgunz

asked Nov 24 '18 at 8:59

gbgunz

asked Nov 24 '18 at 8:59

gbgunz

add a comment |

1 Answer
1

active

oldest

votes

If we suppose you have a Dataframe (df), you can use native SQL to extract a new Dataframe (ndf) which could contain the results that you want.

Try this :

df.registerTempTable("df");



Dataframe ndf = sqlContext.sql("SELECT ..... FROM df WHERE ...");

answered Nov 24 '18 at 9:36

Stavros Stilos

Thanks..Normally works, but this doesn't retain the original schema in case of nested array of struct fields...extact requirement in the orginal question here - stackoverflow.com/questions/36476358/…

– gbgunz
Nov 24 '18 at 10:02

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

If we suppose you have a Dataframe (df), you can use native SQL to extract a new Dataframe (ndf) which could contain the results that you want.

Try this :

df.registerTempTable("df");



Dataframe ndf = sqlContext.sql("SELECT ..... FROM df WHERE ...");

answered Nov 24 '18 at 9:36

Stavros Stilos

Thanks..Normally works, but this doesn't retain the original schema in case of nested array of struct fields...extact requirement in the orginal question here - stackoverflow.com/questions/36476358/…

– gbgunz
Nov 24 '18 at 10:02

add a comment |

If we suppose you have a Dataframe (df), you can use native SQL to extract a new Dataframe (ndf) which could contain the results that you want.

Try this :

df.registerTempTable("df");



Dataframe ndf = sqlContext.sql("SELECT ..... FROM df WHERE ...");

answered Nov 24 '18 at 9:36

Stavros Stilos

Thanks..Normally works, but this doesn't retain the original schema in case of nested array of struct fields...extact requirement in the orginal question here - stackoverflow.com/questions/36476358/…

– gbgunz
Nov 24 '18 at 10:02

add a comment |

If we suppose you have a Dataframe (df), you can use native SQL to extract a new Dataframe (ndf) which could contain the results that you want.

Try this :

df.registerTempTable("df");



Dataframe ndf = sqlContext.sql("SELECT ..... FROM df WHERE ...");

answered Nov 24 '18 at 9:36

Stavros Stilos

If we suppose you have a Dataframe (df), you can use native SQL to extract a new Dataframe (ndf) which could contain the results that you want.

Try this :

df.registerTempTable("df");



Dataframe ndf = sqlContext.sql("SELECT ..... FROM df WHERE ...");

answered Nov 24 '18 at 9:36

Stavros Stilos

answered Nov 24 '18 at 9:36

Stavros Stilos

answered Nov 24 '18 at 9:36

Stavros Stilos

answered Nov 24 '18 at 9:36

Stavros Stilos

Thanks..Normally works, but this doesn't retain the original schema in case of nested array of struct fields...extact requirement in the orginal question here - stackoverflow.com/questions/36476358/…

– gbgunz
Nov 24 '18 at 10:02

add a comment |

Thanks..Normally works, but this doesn't retain the original schema in case of nested array of struct fields...extact requirement in the orginal question here - stackoverflow.com/questions/36476358/…

– gbgunz
Nov 24 '18 at 10:02

Thanks..Normally works, but this doesn't retain the original schema in case of nested array of struct fields...extact requirement in the orginal question here - stackoverflow.com/questions/36476358/…

– gbgunz
Nov 24 '18 at 10:02

add a comment |

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