public java.lang.String getMlUseColumnSpecId() {
    java.lang.Object ref = mlUseColumnSpecId_;
    if (ref instanceof java.lang.String) {
      return (java.lang.String) ref;
    } else {
      com.google.protobuf.ByteString bs = (com.google.protobuf.ByteString) ref;
      java.lang.String s = bs.toStringUtf8();
      mlUseColumnSpecId_ = s;
      return s;
    }
  }
public java . lang . String getMlUseColumnSpecId ( ) { java . lang . Object ref = mlUseColumnSpecId_ ; if ( ref instanceof java . lang . String ) { return ( java . lang . String ) ref ; } else { com . google . protobuf . ByteString bs = ( com . google . protobuf . ByteString ) ref ; java . lang . String s = bs . toStringUtf8 ( ) ; mlUseColumnSpecId_ = s ; return s ; } }
<pre>
column_spec_id of the primary table column which specifies a possible ML
use of the row, i.e. the column will be used to split the rows into TRAIN,
VALIDATE and TEST sets.
Required type: STRING.
This column, if set, must either have all of `TRAIN`, `VALIDATE`, `TEST`
among its values, or only have `TEST`, `UNASSIGNED` values. In the latter
case the rows with `UNASSIGNED` value will be assigned by AutoML. Note
that if a given ml use distribution makes it impossible to create a "good"
model, that call will error describing the issue.
If both this column_spec_id and primary table's time_column_spec_id are not
set, then all rows are treated as `UNASSIGNED`.
NOTE: Updates of this field will instantly affect any other users
concurrently working with the dataset.
</pre>

<code>string ml_use_column_spec_id = 4;</code>