zipWithIndex gives you global indices, which is not what you want. You'll want to use flatMap with a map function that iterates through each iterable and returns the (String, Int, String) tuple for each element.
On Thu, Jul 30, 2015 at 4:13 AM, askformore [via Apache Spark User List] < ml-node+s1001560n24071...@n3.nabble.com> wrote: > I have some data like this: RDD[(String, String)] = ((*key-1*, a), ( > *key-1*,b), (*key-2*,a), (*key-2*,c),(*key-3*,b),(*key-4*,d)) and I want > to group the data by Key, and for each group, add index fields to the > groupmember, at last I can transform the data to below : RDD[(String, > *Int*, String)] = ((key-1,*1*, a), (key-1,*2,*b), (key-2,*1*,a), (key-2, > *2*,b),(key-3,*1*,b),(key-4,*1*,d)) I tried to groupByKey firstly, then I > got a RDD[(String, Iterable[String])], but I don't know how to use > zipWithIndex function to each Iterable... thanks. > > ------------------------------ > If you reply to this email, your message will be added to the discussion > below: > > http://apache-spark-user-list.1001560.n3.nabble.com/help-plz-how-to-use-zipWithIndex-to-each-subset-of-a-RDD-tp24071.html > To start a new topic under Apache Spark User List, email > ml-node+s1001560n1...@n3.nabble.com > To unsubscribe from Apache Spark User List, click here > <http://apache-spark-user-list.1001560.n3.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_code&node=1&code=cm9rcm9za2FyQGdtYWlsLmNvbXwxfC0xNDM4OTI3NjU3> > . > NAML > <http://apache-spark-user-list.1001560.n3.nabble.com/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml> > -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/help-plz-how-to-use-zipWithIndex-to-each-subset-of-a-RDD-tp24071p24074.html Sent from the Apache Spark User List mailing list archive at Nabble.com.