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Posted to user@spark.apache.org by Olivier Girardot <ss...@gmail.com> on 2015/07/01 12:07:18 UTC
Re: Check for null in PySpark DataFrame
I must admit I've been using the same "back to SQL" strategy for now :p
So I'd be glad to have insights into that too.
Le mar. 30 juin 2015 à 23:28, pedro <sk...@gmail.com> a écrit :
> I am trying to find what is the correct way to programmatically check for
> null values for rows in a dataframe. For example, below is the code using
> pyspark and sql:
>
> df = sqlContext.createDataFrame(sc.parallelize([(1, None), (2, "a"), (3,
> "b"), (4, None)]))
> df.where('_2 is not null').count()
>
> However, this won't work
> df.where(df._2 != None).count()
>
> It seems there is no native Python way with DataFrames to do this, but I
> find that difficult to believe and more likely that I am missing the "right
> way" to do this.
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/Check-for-null-in-PySpark-DataFrame-tp23553.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
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Re: Check for null in PySpark DataFrame
Posted by Pedro Rodriguez <sk...@gmail.com>.
Thanks for the tip. Any idea why the intuitive answer doesn't work ( !=
None)? I inspected the Row columns and they do indeed have a None value. I
would suspect that somehow Python's None is translated to something in jvm
which doesn't equal to null?
I might check out the source code for a better idea as well
Pedro
On Wed, Jul 1, 2015 at 12:18 PM, Michael Armbrust <mi...@databricks.com>
wrote:
> There is an isNotNull function on any column.
>
> df._1.isNotNull
>
> or
>
> from pyspark.sql.functions import *
> col("myColumn").isNotNull
>
> On Wed, Jul 1, 2015 at 3:07 AM, Olivier Girardot <ss...@gmail.com>
> wrote:
>
>> I must admit I've been using the same "back to SQL" strategy for now :p
>> So I'd be glad to have insights into that too.
>>
>> Le mar. 30 juin 2015 à 23:28, pedro <sk...@gmail.com> a écrit :
>>
>>> I am trying to find what is the correct way to programmatically check for
>>> null values for rows in a dataframe. For example, below is the code using
>>> pyspark and sql:
>>>
>>> df = sqlContext.createDataFrame(sc.parallelize([(1, None), (2, "a"), (3,
>>> "b"), (4, None)]))
>>> df.where('_2 is not null').count()
>>>
>>> However, this won't work
>>> df.where(df._2 != None).count()
>>>
>>> It seems there is no native Python way with DataFrames to do this, but I
>>> find that difficult to believe and more likely that I am missing the
>>> "right
>>> way" to do this.
>>>
>>>
>>>
>>> --
>>> View this message in context:
>>> http://apache-spark-user-list.1001560.n3.nabble.com/Check-for-null-in-PySpark-DataFrame-tp23553.html
>>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>>>
>>> ---------------------------------------------------------------------
>>> To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
>>> For additional commands, e-mail: user-help@spark.apache.org
>>>
>>>
>
--
Pedro Rodriguez
UCBerkeley 2014 | Computer Science
SnowGeek <http://SnowGeek.org>
pedro-rodriguez.com
ski.rodriguez@gmail.com
208-340-1703
Re: Check for null in PySpark DataFrame
Posted by Michael Armbrust <mi...@databricks.com>.
There is an isNotNull function on any column.
df._1.isNotNull
or
from pyspark.sql.functions import *
col("myColumn").isNotNull
On Wed, Jul 1, 2015 at 3:07 AM, Olivier Girardot <ss...@gmail.com> wrote:
> I must admit I've been using the same "back to SQL" strategy for now :p
> So I'd be glad to have insights into that too.
>
> Le mar. 30 juin 2015 à 23:28, pedro <sk...@gmail.com> a écrit :
>
>> I am trying to find what is the correct way to programmatically check for
>> null values for rows in a dataframe. For example, below is the code using
>> pyspark and sql:
>>
>> df = sqlContext.createDataFrame(sc.parallelize([(1, None), (2, "a"), (3,
>> "b"), (4, None)]))
>> df.where('_2 is not null').count()
>>
>> However, this won't work
>> df.where(df._2 != None).count()
>>
>> It seems there is no native Python way with DataFrames to do this, but I
>> find that difficult to believe and more likely that I am missing the
>> "right
>> way" to do this.
>>
>>
>>
>> --
>> View this message in context:
>> http://apache-spark-user-list.1001560.n3.nabble.com/Check-for-null-in-PySpark-DataFrame-tp23553.html
>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>>
>> ---------------------------------------------------------------------
>> To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
>> For additional commands, e-mail: user-help@spark.apache.org
>>
>>