Same column names in Spark DataFrame supported, but how to select individually

Same column names in Spark DataFrame supported, but how to select individually - non JOINed scenario

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Given that we can see the same Col name in a dataframe below - as I noted elsewhere:

root

  |-- week: string (nullable = true)

  |-- dim1: integer (nullable = false)

  |-- dim2: string (nullable = true)

  |-- t1: integer (nullable = false)

  |-- t2: integer (nullable = false)

  |-- t3: integer (nullable = false)

  |-- t1: integer (nullable = false)

  |-- t2: integer (nullable = false)

  |-- t3: integer (nullable = false)

  |-- t1_diff: integer (nullable = false)

  |-- t2_diff: integer (nullable = false)

and that:

df.select("t1").show(false)

returns ambiguous reference, then how can I state which one I want to select?

This is not a result of a JOIN, but just based on a Seq definition with .toDF(...) as follows:

val df = Seq(

         ("2016-04-02",14, null, 9784, 880, 23, 9789, 820, 45, -5, 60),

         ("2016-04-30",14, "FR", 9785,  13, 34, 9785,   9, 67, 90, 4),

         ("2016-04-16",14, "FR", 9785,  13, 34, 9785,   9, 67, -100, -123)

            ).toDF("week", "dim1", "dim2", "t1", "t2", "t3", "t1", "t2", "t3", "t1_diff", "t2_diff")

Somewhat inconsistent to me, and not something I would do, but I did note this, so more so out of curiosity. Seems an oversight?

edited Nov 17 at 14:31

asked Nov 17 at 14:18

thebluephantom

2,0832823

add a comment |

up vote
0
down vote

favorite

Given that we can see the same Col name in a dataframe below - as I noted elsewhere:

root

  |-- week: string (nullable = true)

  |-- dim1: integer (nullable = false)

  |-- dim2: string (nullable = true)

  |-- t1: integer (nullable = false)

  |-- t2: integer (nullable = false)

  |-- t3: integer (nullable = false)

  |-- t1: integer (nullable = false)

  |-- t2: integer (nullable = false)

  |-- t3: integer (nullable = false)

  |-- t1_diff: integer (nullable = false)

  |-- t2_diff: integer (nullable = false)

and that:

df.select("t1").show(false)

returns ambiguous reference, then how can I state which one I want to select?

This is not a result of a JOIN, but just based on a Seq definition with .toDF(...) as follows:

val df = Seq(

         ("2016-04-02",14, null, 9784, 880, 23, 9789, 820, 45, -5, 60),

         ("2016-04-30",14, "FR", 9785,  13, 34, 9785,   9, 67, 90, 4),

         ("2016-04-16",14, "FR", 9785,  13, 34, 9785,   9, 67, -100, -123)

            ).toDF("week", "dim1", "dim2", "t1", "t2", "t3", "t1", "t2", "t3", "t1_diff", "t2_diff")

Somewhat inconsistent to me, and not something I would do, but I did note this, so more so out of curiosity. Seems an oversight?

edited Nov 17 at 14:31

asked Nov 17 at 14:18

thebluephantom

2,0832823

add a comment |

up vote
0
down vote

favorite

Given that we can see the same Col name in a dataframe below - as I noted elsewhere:

root

  |-- week: string (nullable = true)

  |-- dim1: integer (nullable = false)

  |-- dim2: string (nullable = true)

  |-- t1: integer (nullable = false)

  |-- t2: integer (nullable = false)

  |-- t3: integer (nullable = false)

  |-- t1: integer (nullable = false)

  |-- t2: integer (nullable = false)

  |-- t3: integer (nullable = false)

  |-- t1_diff: integer (nullable = false)

  |-- t2_diff: integer (nullable = false)

and that:

df.select("t1").show(false)

returns ambiguous reference, then how can I state which one I want to select?

This is not a result of a JOIN, but just based on a Seq definition with .toDF(...) as follows:

val df = Seq(

         ("2016-04-02",14, null, 9784, 880, 23, 9789, 820, 45, -5, 60),

         ("2016-04-30",14, "FR", 9785,  13, 34, 9785,   9, 67, 90, 4),

         ("2016-04-16",14, "FR", 9785,  13, 34, 9785,   9, 67, -100, -123)

            ).toDF("week", "dim1", "dim2", "t1", "t2", "t3", "t1", "t2", "t3", "t1_diff", "t2_diff")

Somewhat inconsistent to me, and not something I would do, but I did note this, so more so out of curiosity. Seems an oversight?

edited Nov 17 at 14:31

asked Nov 17 at 14:18

thebluephantom

2,0832823

Given that we can see the same Col name in a dataframe below - as I noted elsewhere:

root

  |-- week: string (nullable = true)

  |-- dim1: integer (nullable = false)

  |-- dim2: string (nullable = true)

  |-- t1: integer (nullable = false)

  |-- t2: integer (nullable = false)

  |-- t3: integer (nullable = false)

  |-- t1: integer (nullable = false)

  |-- t2: integer (nullable = false)

  |-- t3: integer (nullable = false)

  |-- t1_diff: integer (nullable = false)

  |-- t2_diff: integer (nullable = false)

and that:

df.select("t1").show(false)

returns ambiguous reference, then how can I state which one I want to select?

This is not a result of a JOIN, but just based on a Seq definition with .toDF(...) as follows:

val df = Seq(

         ("2016-04-02",14, null, 9784, 880, 23, 9789, 820, 45, -5, 60),

         ("2016-04-30",14, "FR", 9785,  13, 34, 9785,   9, 67, 90, 4),

         ("2016-04-16",14, "FR", 9785,  13, 34, 9785,   9, 67, -100, -123)

            ).toDF("week", "dim1", "dim2", "t1", "t2", "t3", "t1", "t2", "t3", "t1_diff", "t2_diff")

Somewhat inconsistent to me, and not something I would do, but I did note this, so more so out of curiosity. Seems an oversight?

apache-spark

edited Nov 17 at 14:31

asked Nov 17 at 14:18

thebluephantom

2,0832823

edited Nov 17 at 14:31

asked Nov 17 at 14:18

thebluephantom

2,0832823

edited Nov 17 at 14:31

asked Nov 17 at 14:18

thebluephantom

2,0832823

asked Nov 17 at 14:18

thebluephantom

2,0832823

asked Nov 17 at 14:18

thebluephantom

2,0832823

add a comment |

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