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Posted to user@spark.apache.org by Mich Talebzadeh <mi...@gmail.com> on 2021/12/15 11:23:58 UTC
class instance variable in PySpark used in lambda function
Hi,
I define class instance variable self.numRows = 10 to be available to all
methods of this cls as below
class RandomData:
def __init__(self, spark_session, spark_context):
self.spark = spark_session
self.sc = spark_context
self.config = config
self.values = dict()
*self.numRows = 10*
In another method of the same class, I use lambda function to generate
random values
def generateRamdomData(self):
rdd = self.sc.parallelize(Range). \
map(lambda x: (x, uf.clustered(x, *self.numRows*), \
This fails with the error below
Could not serialize object: Exception: It appears that you are attempting
to reference SparkContext from a broadcast variable, action, or
transformation. SparkContext can only be used on the driver, not in code
that it run on workers. For more information, see SPARK-5063.
However this works if I assign self.numRows to a local variable in the that
method as below
*numRows = self.numRows*
rdd = self.sc.parallelize(Range). \
map(lambda x: (x, uf.clustered(x, *numRows*), \
Any better explanation
Thanks
view my Linkedin profile
<https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
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loss, damage or destruction of data or any other property which may arise
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Re: class instance variable in PySpark used in lambda function
Posted by Mich Talebzadeh <mi...@gmail.com>.
Thanks Timothy for your inference and Gary for the correction. You made my
day 😁.
Regards
view my Linkedin profile
<https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
*Disclaimer:* Use it at your own risk. Any and all responsibility for any
loss, damage or destruction of data or any other property which may arise
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The author will in no case be liable for any monetary damages arising from
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On Fri, 17 Dec 2021 at 00:27, Gary Liu <ga...@gmail.com> wrote:
> Thank you for the clarification.
>
> I hate auto correction of the keyboard on my phone.
>
> On Thu, Dec 16, 2021 at 17:37 Timothy Peng <sh...@gmail.com> wrote:
>
>> It’s Holden not Golden. She is an active contributor in Spark project.
>>
>>
>>> Just read a book discussing this(Learning Spark, by Golden Karau, Andy
>>> Konwinski etc).
>>>
>>> As you use self in your rdd, the whole RandomData object need to be
>>> sent to worker nodes, and sometimes Python don't know how to pickle it and
>>> throw an error out.
>>>
>>>
>>>
>>> On Thu, Dec 16, 2021 at 14:26 Mich Talebzadeh <mi...@gmail.com>
>>> wrote:
>>>
>>>> Many thanks Pol.
>>>>
>>>> As it happens I was doing a work around with numRows = 10. In general
>>>> it is bad practice to hard code the constants within the code. For the same
>>>> reason we ought not put URLs embedded in the PySpark program itself.
>>>>
>>>> What I did was to add numRows to the yaml file which is read at the
>>>> beginning. It is basically number of rows of random numbers to be generated
>>>> in PySpark and posted to the database. That was the solution I adopted.
>>>>
>>>> Cheers,
>>>>
>>>> Mich
>>>>
>>>>
>>>>
>>>> view my Linkedin profile
>>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>>
>>>>
>>>>
>>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>>> any loss, damage or destruction of data or any other property which may
>>>> arise from relying on this email's technical content is explicitly
>>>> disclaimed. The author will in no case be liable for any monetary damages
>>>> arising from such loss, damage or destruction.
>>>>
>>>>
>>>>
>>>>
>>>> On Wed, 15 Dec 2021 at 12:03, Pol Santamaria <po...@qbeast.io> wrote:
>>>>
>>>>> To me it looks like you are accessing "self" on the workers by using
>>>>> "self.numRows" inside the map. As a consequence, "self" needs to be
>>>>> serialized which has an attribute referencing the "sparkContext", thus
>>>>> trying to serialize the context and failing.
>>>>>
>>>>> It can be solved in different ways, for instance by avoiding the use
>>>>> of "self" in the map, as you did in the last snippet, or by saving the
>>>>> spark context / session in a different class than "numRows".
>>>>>
>>>>> Bests,
>>>>>
>>>>> Pol Santamaria
>>>>>
>>>>>
>>>>> On Wed, Dec 15, 2021 at 12:24 PM Mich Talebzadeh <
>>>>> mich.talebzadeh@gmail.com> wrote:
>>>>>
>>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> I define class instance variable self.numRows = 10 to be available
>>>>>> to all methods of this cls as below
>>>>>>
>>>>>> class RandomData:
>>>>>> def __init__(self, spark_session, spark_context):
>>>>>> self.spark = spark_session
>>>>>> self.sc = spark_context
>>>>>> self.config = config
>>>>>> self.values = dict()
>>>>>> *self.numRows = 10*
>>>>>>
>>>>>> In another method of the same class, I use lambda function to
>>>>>> generate random values
>>>>>>
>>>>>> def generateRamdomData(self):
>>>>>> rdd = self.sc.parallelize(Range). \
>>>>>> map(lambda x: (x, uf.clustered(x, *self.numRows*), \
>>>>>>
>>>>>> This fails with the error below
>>>>>>
>>>>>> Could not serialize object: Exception: It appears that you are
>>>>>> attempting to reference SparkContext from a broadcast variable, action, or
>>>>>> transformation. SparkContext can only be used on the driver, not in code
>>>>>> that it run on workers. For more information, see SPARK-5063.
>>>>>>
>>>>>> However this works if I assign self.numRows to a local variable in
>>>>>> the that method as below
>>>>>>
>>>>>>
>>>>>> *numRows = self.numRows*
>>>>>> rdd = self.sc.parallelize(Range). \
>>>>>> map(lambda x: (x, uf.clustered(x, *numRows*), \
>>>>>>
>>>>>>
>>>>>>
>>>>>> Any better explanation
>>>>>>
>>>>>>
>>>>>> Thanks
>>>>>>
>>>>>>
>>>>>> view my Linkedin profile
>>>>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>>>>
>>>>>>
>>>>>>
>>>>>> *Disclaimer:* Use it at your own risk. Any and all responsibility
>>>>>> for any loss, damage or destruction of data or any other property which may
>>>>>> arise from relying on this email's technical content is explicitly
>>>>>> disclaimed. The author will in no case be liable for any monetary damages
>>>>>> arising from such loss, damage or destruction.
>>>>>>
>>>>>>
>>>>>>
>>>>> --
>>> Gary Liu
>>>
>> --
> Gary Liu
>
Re: class instance variable in PySpark used in lambda function
Posted by Gary Liu <ga...@gmail.com>.
Thank you for the clarification.
I hate auto correction of the keyboard on my phone.
On Thu, Dec 16, 2021 at 17:37 Timothy Peng <sh...@gmail.com> wrote:
> It’s Holden not Golden. She is an active contributor in Spark project.
>
>
>> Just read a book discussing this(Learning Spark, by Golden Karau, Andy
>> Konwinski etc).
>>
>> As you use self in your rdd, the whole RandomData object need to be sent
>> to worker nodes, and sometimes Python don't know how to pickle it and throw
>> an error out.
>>
>>
>>
>> On Thu, Dec 16, 2021 at 14:26 Mich Talebzadeh <mi...@gmail.com>
>> wrote:
>>
>>> Many thanks Pol.
>>>
>>> As it happens I was doing a work around with numRows = 10. In general
>>> it is bad practice to hard code the constants within the code. For the same
>>> reason we ought not put URLs embedded in the PySpark program itself.
>>>
>>> What I did was to add numRows to the yaml file which is read at the
>>> beginning. It is basically number of rows of random numbers to be generated
>>> in PySpark and posted to the database. That was the solution I adopted.
>>>
>>> Cheers,
>>>
>>> Mich
>>>
>>>
>>>
>>> view my Linkedin profile
>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>
>>>
>>>
>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>> any loss, damage or destruction of data or any other property which may
>>> arise from relying on this email's technical content is explicitly
>>> disclaimed. The author will in no case be liable for any monetary damages
>>> arising from such loss, damage or destruction.
>>>
>>>
>>>
>>>
>>> On Wed, 15 Dec 2021 at 12:03, Pol Santamaria <po...@qbeast.io> wrote:
>>>
>>>> To me it looks like you are accessing "self" on the workers by using
>>>> "self.numRows" inside the map. As a consequence, "self" needs to be
>>>> serialized which has an attribute referencing the "sparkContext", thus
>>>> trying to serialize the context and failing.
>>>>
>>>> It can be solved in different ways, for instance by avoiding the use of
>>>> "self" in the map, as you did in the last snippet, or by saving the spark
>>>> context / session in a different class than "numRows".
>>>>
>>>> Bests,
>>>>
>>>> Pol Santamaria
>>>>
>>>>
>>>> On Wed, Dec 15, 2021 at 12:24 PM Mich Talebzadeh <
>>>> mich.talebzadeh@gmail.com> wrote:
>>>>
>>>>>
>>>>> Hi,
>>>>>
>>>>> I define class instance variable self.numRows = 10 to be available to
>>>>> all methods of this cls as below
>>>>>
>>>>> class RandomData:
>>>>> def __init__(self, spark_session, spark_context):
>>>>> self.spark = spark_session
>>>>> self.sc = spark_context
>>>>> self.config = config
>>>>> self.values = dict()
>>>>> *self.numRows = 10*
>>>>>
>>>>> In another method of the same class, I use lambda function to generate
>>>>> random values
>>>>>
>>>>> def generateRamdomData(self):
>>>>> rdd = self.sc.parallelize(Range). \
>>>>> map(lambda x: (x, uf.clustered(x, *self.numRows*), \
>>>>>
>>>>> This fails with the error below
>>>>>
>>>>> Could not serialize object: Exception: It appears that you are
>>>>> attempting to reference SparkContext from a broadcast variable, action, or
>>>>> transformation. SparkContext can only be used on the driver, not in code
>>>>> that it run on workers. For more information, see SPARK-5063.
>>>>>
>>>>> However this works if I assign self.numRows to a local variable in
>>>>> the that method as below
>>>>>
>>>>>
>>>>> *numRows = self.numRows*
>>>>> rdd = self.sc.parallelize(Range). \
>>>>> map(lambda x: (x, uf.clustered(x, *numRows*), \
>>>>>
>>>>>
>>>>>
>>>>> Any better explanation
>>>>>
>>>>>
>>>>> Thanks
>>>>>
>>>>>
>>>>> view my Linkedin profile
>>>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>>>
>>>>>
>>>>>
>>>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>>>> any loss, damage or destruction of data or any other property which may
>>>>> arise from relying on this email's technical content is explicitly
>>>>> disclaimed. The author will in no case be liable for any monetary damages
>>>>> arising from such loss, damage or destruction.
>>>>>
>>>>>
>>>>>
>>>> --
>> Gary Liu
>>
> --
Gary Liu
Re: class instance variable in PySpark used in lambda function
Posted by Timothy Peng <sh...@gmail.com>.
It’s Holden not Golden. She is an active contributor in Spark project.
> Just read a book discussing this(Learning Spark, by Golden Karau, Andy
> Konwinski etc).
>
> As you use self in your rdd, the whole RandomData object need to be sent
> to worker nodes, and sometimes Python don't know how to pickle it and throw
> an error out.
>
>
>
> On Thu, Dec 16, 2021 at 14:26 Mich Talebzadeh <mi...@gmail.com>
> wrote:
>
>> Many thanks Pol.
>>
>> As it happens I was doing a work around with numRows = 10. In general it
>> is bad practice to hard code the constants within the code. For the same
>> reason we ought not put URLs embedded in the PySpark program itself.
>>
>> What I did was to add numRows to the yaml file which is read at the
>> beginning. It is basically number of rows of random numbers to be generated
>> in PySpark and posted to the database. That was the solution I adopted.
>>
>> Cheers,
>>
>> Mich
>>
>>
>>
>> view my Linkedin profile
>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>
>>
>>
>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>> any loss, damage or destruction of data or any other property which may
>> arise from relying on this email's technical content is explicitly
>> disclaimed. The author will in no case be liable for any monetary damages
>> arising from such loss, damage or destruction.
>>
>>
>>
>>
>> On Wed, 15 Dec 2021 at 12:03, Pol Santamaria <po...@qbeast.io> wrote:
>>
>>> To me it looks like you are accessing "self" on the workers by using
>>> "self.numRows" inside the map. As a consequence, "self" needs to be
>>> serialized which has an attribute referencing the "sparkContext", thus
>>> trying to serialize the context and failing.
>>>
>>> It can be solved in different ways, for instance by avoiding the use of
>>> "self" in the map, as you did in the last snippet, or by saving the spark
>>> context / session in a different class than "numRows".
>>>
>>> Bests,
>>>
>>> Pol Santamaria
>>>
>>>
>>> On Wed, Dec 15, 2021 at 12:24 PM Mich Talebzadeh <
>>> mich.talebzadeh@gmail.com> wrote:
>>>
>>>>
>>>> Hi,
>>>>
>>>> I define class instance variable self.numRows = 10 to be available to
>>>> all methods of this cls as below
>>>>
>>>> class RandomData:
>>>> def __init__(self, spark_session, spark_context):
>>>> self.spark = spark_session
>>>> self.sc = spark_context
>>>> self.config = config
>>>> self.values = dict()
>>>> *self.numRows = 10*
>>>>
>>>> In another method of the same class, I use lambda function to generate
>>>> random values
>>>>
>>>> def generateRamdomData(self):
>>>> rdd = self.sc.parallelize(Range). \
>>>> map(lambda x: (x, uf.clustered(x, *self.numRows*), \
>>>>
>>>> This fails with the error below
>>>>
>>>> Could not serialize object: Exception: It appears that you are
>>>> attempting to reference SparkContext from a broadcast variable, action, or
>>>> transformation. SparkContext can only be used on the driver, not in code
>>>> that it run on workers. For more information, see SPARK-5063.
>>>>
>>>> However this works if I assign self.numRows to a local variable in the
>>>> that method as below
>>>>
>>>>
>>>> *numRows = self.numRows*
>>>> rdd = self.sc.parallelize(Range). \
>>>> map(lambda x: (x, uf.clustered(x, *numRows*), \
>>>>
>>>>
>>>>
>>>> Any better explanation
>>>>
>>>>
>>>> Thanks
>>>>
>>>>
>>>> view my Linkedin profile
>>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>>
>>>>
>>>>
>>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>>> any loss, damage or destruction of data or any other property which may
>>>> arise from relying on this email's technical content is explicitly
>>>> disclaimed. The author will in no case be liable for any monetary damages
>>>> arising from such loss, damage or destruction.
>>>>
>>>>
>>>>
>>> --
> Gary Liu
>
Re: class instance variable in PySpark used in lambda function
Posted by Gary Liu <ga...@gmail.com>.
Just read a book discussing this(Learning Spark, by Golden Karau, Andy
Konwinski etc).
As you use self in your rdd, the whole RandomData object need to be sent
to worker nodes, and sometimes Python don't know how to pickle it and throw
an error out.
On Thu, Dec 16, 2021 at 14:26 Mich Talebzadeh <mi...@gmail.com>
wrote:
> Many thanks Pol.
>
> As it happens I was doing a work around with numRows = 10. In general it
> is bad practice to hard code the constants within the code. For the same
> reason we ought not put URLs embedded in the PySpark program itself.
>
> What I did was to add numRows to the yaml file which is read at the
> beginning. It is basically number of rows of random numbers to be generated
> in PySpark and posted to the database. That was the solution I adopted.
>
> Cheers,
>
> Mich
>
>
>
> view my Linkedin profile
> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
> On Wed, 15 Dec 2021 at 12:03, Pol Santamaria <po...@qbeast.io> wrote:
>
>> To me it looks like you are accessing "self" on the workers by using
>> "self.numRows" inside the map. As a consequence, "self" needs to be
>> serialized which has an attribute referencing the "sparkContext", thus
>> trying to serialize the context and failing.
>>
>> It can be solved in different ways, for instance by avoiding the use of
>> "self" in the map, as you did in the last snippet, or by saving the spark
>> context / session in a different class than "numRows".
>>
>> Bests,
>>
>> Pol Santamaria
>>
>>
>> On Wed, Dec 15, 2021 at 12:24 PM Mich Talebzadeh <
>> mich.talebzadeh@gmail.com> wrote:
>>
>>>
>>> Hi,
>>>
>>> I define class instance variable self.numRows = 10 to be available to
>>> all methods of this cls as below
>>>
>>> class RandomData:
>>> def __init__(self, spark_session, spark_context):
>>> self.spark = spark_session
>>> self.sc = spark_context
>>> self.config = config
>>> self.values = dict()
>>> *self.numRows = 10*
>>>
>>> In another method of the same class, I use lambda function to generate
>>> random values
>>>
>>> def generateRamdomData(self):
>>> rdd = self.sc.parallelize(Range). \
>>> map(lambda x: (x, uf.clustered(x, *self.numRows*), \
>>>
>>> This fails with the error below
>>>
>>> Could not serialize object: Exception: It appears that you are
>>> attempting to reference SparkContext from a broadcast variable, action, or
>>> transformation. SparkContext can only be used on the driver, not in code
>>> that it run on workers. For more information, see SPARK-5063.
>>>
>>> However this works if I assign self.numRows to a local variable in the
>>> that method as below
>>>
>>>
>>> *numRows = self.numRows*
>>> rdd = self.sc.parallelize(Range). \
>>> map(lambda x: (x, uf.clustered(x, *numRows*), \
>>>
>>>
>>>
>>> Any better explanation
>>>
>>>
>>> Thanks
>>>
>>>
>>> view my Linkedin profile
>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>
>>>
>>>
>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>> any loss, damage or destruction of data or any other property which may
>>> arise from relying on this email's technical content is explicitly
>>> disclaimed. The author will in no case be liable for any monetary damages
>>> arising from such loss, damage or destruction.
>>>
>>>
>>>
>> --
Gary Liu
Re: class instance variable in PySpark used in lambda function
Posted by Mich Talebzadeh <mi...@gmail.com>.
Many thanks Pol.
As it happens I was doing a work around with numRows = 10. In general it
is bad practice to hard code the constants within the code. For the same
reason we ought not put URLs embedded in the PySpark program itself.
What I did was to add numRows to the yaml file which is read at the
beginning. It is basically number of rows of random numbers to be generated
in PySpark and posted to the database. That was the solution I adopted.
Cheers,
Mich
view my Linkedin profile
<https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
*Disclaimer:* Use it at your own risk. Any and all responsibility for any
loss, damage or destruction of data or any other property which may arise
from relying on this email's technical content is explicitly disclaimed.
The author will in no case be liable for any monetary damages arising from
such loss, damage or destruction.
On Wed, 15 Dec 2021 at 12:03, Pol Santamaria <po...@qbeast.io> wrote:
> To me it looks like you are accessing "self" on the workers by using
> "self.numRows" inside the map. As a consequence, "self" needs to be
> serialized which has an attribute referencing the "sparkContext", thus
> trying to serialize the context and failing.
>
> It can be solved in different ways, for instance by avoiding the use of
> "self" in the map, as you did in the last snippet, or by saving the spark
> context / session in a different class than "numRows".
>
> Bests,
>
> Pol Santamaria
>
>
> On Wed, Dec 15, 2021 at 12:24 PM Mich Talebzadeh <
> mich.talebzadeh@gmail.com> wrote:
>
>>
>> Hi,
>>
>> I define class instance variable self.numRows = 10 to be available to
>> all methods of this cls as below
>>
>> class RandomData:
>> def __init__(self, spark_session, spark_context):
>> self.spark = spark_session
>> self.sc = spark_context
>> self.config = config
>> self.values = dict()
>> *self.numRows = 10*
>>
>> In another method of the same class, I use lambda function to generate
>> random values
>>
>> def generateRamdomData(self):
>> rdd = self.sc.parallelize(Range). \
>> map(lambda x: (x, uf.clustered(x, *self.numRows*), \
>>
>> This fails with the error below
>>
>> Could not serialize object: Exception: It appears that you are attempting
>> to reference SparkContext from a broadcast variable, action, or
>> transformation. SparkContext can only be used on the driver, not in code
>> that it run on workers. For more information, see SPARK-5063.
>>
>> However this works if I assign self.numRows to a local variable in the
>> that method as below
>>
>>
>> *numRows = self.numRows*
>> rdd = self.sc.parallelize(Range). \
>> map(lambda x: (x, uf.clustered(x, *numRows*), \
>>
>>
>>
>> Any better explanation
>>
>>
>> Thanks
>>
>>
>> view my Linkedin profile
>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>
>>
>>
>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>> any loss, damage or destruction of data or any other property which may
>> arise from relying on this email's technical content is explicitly
>> disclaimed. The author will in no case be liable for any monetary damages
>> arising from such loss, damage or destruction.
>>
>>
>>
>
Re: class instance variable in PySpark used in lambda function
Posted by Pol Santamaria <po...@qbeast.io>.
To me it looks like you are accessing "self" on the workers by using
"self.numRows" inside the map. As a consequence, "self" needs to be
serialized which has an attribute referencing the "sparkContext", thus
trying to serialize the context and failing.
It can be solved in different ways, for instance by avoiding the use of
"self" in the map, as you did in the last snippet, or by saving the spark
context / session in a different class than "numRows".
Bests,
Pol Santamaria
On Wed, Dec 15, 2021 at 12:24 PM Mich Talebzadeh <mi...@gmail.com>
wrote:
>
> Hi,
>
> I define class instance variable self.numRows = 10 to be available to all
> methods of this cls as below
>
> class RandomData:
> def __init__(self, spark_session, spark_context):
> self.spark = spark_session
> self.sc = spark_context
> self.config = config
> self.values = dict()
> *self.numRows = 10*
>
> In another method of the same class, I use lambda function to generate
> random values
>
> def generateRamdomData(self):
> rdd = self.sc.parallelize(Range). \
> map(lambda x: (x, uf.clustered(x, *self.numRows*), \
>
> This fails with the error below
>
> Could not serialize object: Exception: It appears that you are attempting
> to reference SparkContext from a broadcast variable, action, or
> transformation. SparkContext can only be used on the driver, not in code
> that it run on workers. For more information, see SPARK-5063.
>
> However this works if I assign self.numRows to a local variable in the
> that method as below
>
>
> *numRows = self.numRows*
> rdd = self.sc.parallelize(Range). \
> map(lambda x: (x, uf.clustered(x, *numRows*), \
>
>
>
> Any better explanation
>
>
> Thanks
>
>
> view my Linkedin profile
> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>