My Schema:
|-- Canonical_URL: string (nullable = true)
|-- Certifications: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- Certification_Authority: string (nullable = true)
| | |-- End: string (nullable = true)
| | |-- License: string (nullable = true)
| | |-- Start: string (nullable = true)
| | |-- Title: string (nullable = true)
|-- CompanyId: string (nullable = true)
|-- Country: string (nullable = true)
|-- vendorTags: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- score: double (nullable = true)
| | |-- vendor: string (nullable = true)
I tried the below query to select nested fields from vendorTags
df3 = sqlContext.sql("select vendorTags.vendor from globalcontacts")
How can I query the nested fields in where clause like below in PySpark
df3 = sqlContext.sql("select vendorTags.vendor from globalcontacts where vendorTags.vendor = 'alpha'")
or
df3 = sqlContext.sql("select vendorTags.vendor from globalcontacts where vendorTags.score > 123.123456")
something like this..
I tried the above queries only to get the below error
df3 = sqlContext.sql("select vendorTags.vendor from globalcontacts where vendorTags.vendor = 'alpha'")
16/03/15 13:16:02 INFO ParseDriver: Parsing command: select vendorTags.vendor from globalcontacts where vendorTags.vendor = 'alpha'
16/03/15 13:16:03 INFO ParseDriver: Parse Completed
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/spark/python/pyspark/sql/context.py", line 583, in sql
return DataFrame(self._ssql_ctx.sql(sqlQuery), self)
File "/usr/lib/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in __call__
File "/usr/lib/spark/python/pyspark/sql/utils.py", line 51, in deco
raise AnalysisException(s.split(': ', 1)[1], stackTrace)
pyspark.sql.utils.AnalysisException: u"cannot resolve '(vendorTags.vendor = cast(alpha as double))' due to data type mismatch: differing types in '(vendorTags.vendor = cast(alpha as double))' (array<string> and double).; line 1 pos 71"