Skip to main content

Pandas UDF Error: AttributeError: 'NoneType' object has no attribute '_jvm' [duplicate]

I have a pyspark dataframe like this:

+-------+-------+
| level | value |
+-------+-------+
|  1    |   4   |
|  1    |   5   |
|  2    |   2   |
|  2    |   6   |
|  2    |   3   |
+-------+-------+

I have to create a value for every group in level column and save this in lable column. This value for every group must be unique, so I use ObjectId Mongo function to create that. Next dataframe is like this:

+-------+--------+-------+
| level |   lable| value |
+-------+--------+-------+
|  1    |   bb76 |   4   |
|  1    |   bb76 |   5   |
|  2    |   cv86 |   2   |
|  2    |   cv86 |   6   |
|  2    |   cv86 |   3   |
+-------+--------+-------+

Then I must create a dataframe as following:

+-------+-------+
| lable | value |
+-------+-------+
|  bb76 |   9   |
|  cv86 |   11  |
+-------+-------+

To do that, first I used spark groupby:

   def create_objectid():
       a = str(ObjectId())
       return a

   def add_lable(df):
       df = df.cache()
       df.count()
       grouped_df = df.groupby('level').agg(sum(df.value).alias('temp'))
       grouped_df = grouped_df.withColumnRenamed('level', 'level_temp')
       grouped_df = grouped_df.withColumn('lable', udf_create_objectid())
       grouped_df = grouped_df.drop('temp')
       df  = df.join(grouped_df.select('level_temp','lable'), col('level') == col('level_temp'), how="left").drop(grouped_df.level_temp)
       return df

When I used the above code on spark dataframe with 2 millions records, it takes about 155 seconds to finish. I searched and found that spark window has better performance. Then, I changed the last function to this one. Because pandas_udf needs arg, so I just pass one and print it:

@f.pandas_udf("string")
def create_objectid_on_window(v: pd.Series) -> str:
    print('v:',v)
    return str(ObjectId())

def add_lable(df):  
    w = Window.partitionBy('level')
    df = df.withColumn('lable', create_objectid_on_window('level').over(w))
    return df

But after running the program, I receive this error:

AttributeError: 'NoneType' object has no attribute '_jvm'

Would you please guide me how to solve the problem?

Any help is really appreciated.



source https://stackoverflow.com/questions/76300991/pandas-udf-error-attributeerror-nonetype-object-has-no-attribute-jvm

Comments

Popular posts from this blog

How to show number of registered users in Laravel based on usertype?

i'm trying to display data from the database in the admin dashboard i used this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count(); echo $users; ?> and i have successfully get the correct data from the database but what if i want to display a specific data for example in this user table there is "usertype" that specify if the user is normal user or admin i want to user the same code above but to display a specific usertype i tried this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count()->WHERE usertype =admin; echo $users; ?> but it didn't work, what am i doing wrong? source https://stackoverflow.com/questions/68199726/how-to-show-number-of-registered-users-in-laravel-based-on-usertype

Why is my reports service not connecting?

I am trying to pull some data from a Postgres database using Node.js and node-postures but I can't figure out why my service isn't connecting. my routes/index.js file: const express = require('express'); const router = express.Router(); const ordersCountController = require('../controllers/ordersCountController'); const ordersController = require('../controllers/ordersController'); const weeklyReportsController = require('../controllers/weeklyReportsController'); router.get('/orders_count', ordersCountController); router.get('/orders', ordersController); router.get('/weekly_reports', weeklyReportsController); module.exports = router; My controllers/weeklyReportsController.js file: const weeklyReportsService = require('../services/weeklyReportsService'); const weeklyReportsController = async (req, res) => { try { const data = await weeklyReportsService; res.json({data}) console...

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...