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spark sql 列转行
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| df = spark.createDataFrame([ | |
| {'id': 1, u'姓名': u'张三', u'分数': 88, u'科目': u'数学'}, | |
| {'id': 2, u'姓名': u'李雷', u'分数': 67, u'科目': u'数学'}, | |
| {'id': 3, u'姓名': u'宫九', u'分数': 77, u'科目': u'数学'}, | |
| {'id': 4, u'姓名': u'王五', u'分数': 65, u'科目': u'数学'}, | |
| {'id': 1, u'姓名': u'张三', u'分数': 77, u'科目': u'英语'}, | |
| {'id': 2, u'姓名': u'李雷', u'分数': 90, u'科目': u'英语'}, | |
| {'id': 3, u'姓名': u'宫九', u'分数': 24, u'科目': u'英语'}, | |
| {'id': 4, u'姓名': u'王五', u'分数': 90, u'科目': u'英语'}, | |
| {'id': 1, u'姓名': u'张三', u'分数': 33, u'科目': u'语文'}, | |
| {'id': 2, u'姓名': u'李雷', u'分数': 87, u'科目': u'语文'}, | |
| {'id': 3, u'姓名': u'宫九', u'分数': 92, u'科目': u'语文'}, | |
| {'id': 4, u'姓名': u'王五', u'分数': 87, u'科目': u'语文'}, | |
| ]) | |
| df.show() | |
| # +---+----+----+----+ | |
| # | id|分数|姓名|科目| | |
| # +---+----+----+----+ | |
| # | 1| 88|张三|数学| | |
| # | 2| 67|李雷|数学| | |
| # | 3| 77|宫九|数学| | |
| # | 4| 65|王五|数学| | |
| # | 1| 77|张三|英语| | |
| # | 2| 90|李雷|英语| | |
| # | 3| 24|宫九|英语| | |
| # | 4| 90|王五|英语| | |
| # | 1| 33|张三|语文| | |
| # | 2| 87|李雷|语文| | |
| # | 3| 92|宫九|语文| | |
| # | 4| 87|王五|语文| | |
| # +---+----+----+----+ | |
| # spark sql 列转行 | |
| spark_df_pivot = spark.sql(""" | |
| SELECT | |
| * | |
| FROM df | |
| PIVOT | |
| ( | |
| SUM(`分数`) | |
| FOR `科目` in ('数学','英语') | |
| ) | |
| ORDER BY id | |
| """).cache() | |
| spark_df_pivot.show() | |
| # +---+----+----+----+ | |
| # | id|姓名|数学|英语| | |
| # +---+----+----+----+ | |
| # | 1|张三| 88| 77| | |
| # | 2|李雷| 67| 90| | |
| # | 3|宫九| 77| 24| | |
| # | 4|王五| 65| 90| | |
| # +---+----+----+----+ | |
| # spark scala | |
| val spark_scala_pivot = | |
| df.groupBy("id", "姓名") | |
| .pivot("科目") | |
| .agg(sum("分数")) | |
| spark_scala_pivot.show() | |
| # +---+----+----+----+----+ | |
| # | id|姓名|数学|英语|语文| | |
| # +---+----+----+----+----+ | |
| # | 2|李雷| 67| 90| 87| | |
| # | 1|张三| 88| 77| 33| | |
| # | 3|宫九| 77| 24| 92| | |
| # | 4|王五| 65| 90| 87| | |
| # +---+----+----+----+----+ | |
| # hive sql 列转行 | |
| hive_df_pivot = spark.sql(""" | |
| select | |
| id, | |
| `姓名`, | |
| nvl(m ['数学'], 0) as `数学`, | |
| nvl(m ['英语'], 0) as `英语` | |
| from( | |
| select | |
| id, | |
| `姓名`, | |
| collect(`科目`, `分数`) as m | |
| from | |
| df | |
| group by | |
| id, | |
| `姓名` | |
| ) t_b | |
| """).cache() | |
| hive_df_pivot.show() | |
| # id 姓名 数学 英语 | |
| # 4 王五 65 90 | |
| # 1 张三 88 77 | |
| # 2 李雷 67 90 | |
| # 3 宫九 77 24 |
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see how-to-pivot-spark-dataframe
and reshaping-pivoting-data-in-spark-rdd-and-or-spark-dataframes
and sql-ref-syntax-qry-select-pivot