我有两个需要以某种特殊方式连接的数据框。
数据框1:
+--------------------+---------+----------------+
| asset_domain| eid| oid|
+--------------------+---------+----------------+
| test-domain...| 126656| 126656|
| nebraska.aaa.com| 335660| 335660|
| netflix.com| 460| 460|
+--------------------+---------+----------------+
数据框2:
+--------------------+--------------------+---------+--------------+----+----+------------+
| asset| asset_domain|dns_count| ip| ev|post|form_present|
+--------------------+--------------------+---------+--------------+----+----+------------+
| sub1.test-domain...| test-domain...| 6354| 11.11.111.111| 1| 1| null|
| netflix.com| netflix.com| 3836| 22.22.222.222|null|null| null|
+--------------------+--------------------+---------+--------------+----+----+------------+
所需结果:
+--------------------+---------+-------------+----+----+------------+---------+----------------+
| asset|dns_count| ip| ev|post|form_present| eid| oid|
+--------------------+---------+-------------+----+----+------------+---------+----------------+
| netflix.com| 3836|22.22.222.222|null|null| null| 460| 460|
| sub1.test-domain...| 5924|111.11.111.11| 1| 1| null| 126656| 126656|
| nebraska.aaa.com| null| null|null|null| null| 335660| 335660|
+--------------------+---------+-------------+----+----+------------+---------+----------------+
基本上-它应该在asset_domain
上连接df1和df2,但是如果df2中不存在df1和df2,那么生成的asset
应该是df1的asset_domain
。
我尝试了df = df2.join(df1, ["asset_domain"], "right").drop("asset_domain")
,但是显然null
留在了asset
的{{1}}列中,因为它在df2中没有匹配的域。对于这种特殊情况,我该如何将它们添加到nebraska.aaa.com
列中?
答案 0 :(得分:4)
您可以在加入后使用 coalesce
功能创建资产列。
df2.join(df1, ["asset_domain"], "right").select(coalesce("asset","asset_domain").alias("asset"),"dns_count","ip","ev","post","form_present","eid","oid").orderBy("asset").show()
#+----------------+---------+-------------+----+----+------------+------+------+
#| asset|dns_count| ip| ev|post|form_present| eid| oid|
#+----------------+---------+-------------+----+----+------------+------+------+
#|nebraska.aaa.com| null| null|null|null| null|335660|335660|
#| netflix.com| 3836|22.22.222.222|null|null| None| 460| 460|
#|sub1.test-domain| 6354|11.11.111.111| 1| 1| null|126656|126656|
#+----------------+---------+-------------+----+----+------------+------+------+
答案 1 :(得分:0)
加入后,您可以使用isNull()函数
import pyspark.sql.functions as F
tst1 = sqlContext.createDataFrame([('netflix',1),('amazon',2)],schema=("asset_domain",'xtra1'))
tst2= sqlContext.createDataFrame([('netflix','yahoo',1),('amazon','yahoo',2),('flipkart',None,2)],schema=("asset_domain","asset",'xtra'))
tst_j = tst1.join(tst2,on='asset_domain',how='right')
#%%
tst_res = tst_j.withColumn("asset",F.when(F.col('asset').isNull(),F.col('asset_domain')).otherwise(F.col('asset')))