Timeline for Apply GroupByKey to identify the Frequently Products Purchase Together
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 31, 2016 at 10:02 | vote | accept | SaCvP | ||
| Aug 31, 2016 at 10:01 | answer | added | eliasah | timeline score: 0 | |
| Aug 31, 2016 at 9:54 | comment | added | SaCvP | Is there any advantage on using Data Frames? I don't have any constraint on using RDDs but I'm getting a little confusing on my code. I only want to "group" all the products based on transaction_ID | |
| Aug 31, 2016 at 9:46 | comment | added | eliasah | ok why don't you use dataframes ? and spark-csv to read your csv ? is there a constraint on using RDDs ? | |
| Aug 31, 2016 at 9:46 | comment | added | SaCvP | Spark version 1.6.0 | |
| Aug 31, 2016 at 9:39 | comment | added | eliasah | Which version of spark are you using ? | |
| S Aug 31, 2016 at 9:36 | history | suggested | eliasah | CC BY-SA 3.0 |
formatting code
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| Aug 31, 2016 at 9:31 | review | Suggested edits | |||
| S Aug 31, 2016 at 9:36 | |||||
| Aug 30, 2016 at 10:43 | history | asked | SaCvP | CC BY-SA 3.0 |