本文为您介绍如何进行PyODPS的Sequence及执行操作。
前提条件
- 开通MaxCompute。
- 开通DataWorks。
- 在DataWorks上完成创建业务流程,本例使用DataWorks简单模式。详情请参见创建业务流程。
本文为您介绍如何进行PyODPS的Sequence及执行操作。
CREATE TABLE if not exists pyodps_iris
(
sepallength DOUBLE comment '片长度(cm)',
sepalwidth DOUBLE comment '片宽度(cm)',
petallength DOUBLE comment '瓣长度(cm)',
petalwidth DOUBLE comment '瓣宽度(cm)',
name STRING comment '种类'
);
from odps import DataFrame
iris = DataFrame(o.get_table('pyodps_iris'))
#获取列。
print iris.sepallength.head(5)
print iris['sepallength'].head(5)
#查看列的类型。
print iris.sepallength.dtype
#修改列的类型。
iris.sepallength.astype('int')
#计算。
print iris.groupby('name').sepallength.max().head(5)
print iris.sepallength.max()
#重命名列。
print iris.sepalwidth.rename('speal_width').head(5)
#简单的列变化。
print (iris.sepallength + iris.sepalwidth).rename('sum_sepal').head(5)
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 # 片长度(cm)
sepalwidth : double # 片宽度(cm)
petallength : double # 瓣长度(cm)
petalwidth : double # 瓣宽度(cm)
name : string # 种类
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!
from odps import options
from odps import DataFrame
#查看运行时的instance的logview。
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)
#缓存中间Collection结果。
cached = iris[iris.sepalwidth < 3.5].cache()
print cached.head(3)
#异步和并行执行。
from odps.df import Delay
delay = Delay() #创建Delay对象。
df = iris[iris.sepalwidth < 5].cache() #有一个共同的依赖。
future1 = df.sepalwidth.sum().execute(delay=delay) #立即返回future对象,此时并没有执行。
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()
运行结果如下。
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: http://logview.odps.aliyun.com/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: http://logview.odps.aliyun.com/logview/?h=http://service.odps.aliyun.com/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
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