soumilshah1995 commented on issue #8040: URL: https://github.com/apache/hudi/issues/8040#issuecomment-1449098572
i think i have tried deleting column with glue 4.0 and table type as MOR i am getting following error  # Code to other can replicate ``` try: import sys import os from pyspark.context import SparkContext from pyspark.sql.session import SparkSession from awsglue.context import GlueContext from awsglue.job import Job from awsglue.dynamicframe import DynamicFrame from pyspark.sql.functions import col, to_timestamp, monotonically_increasing_id, to_date, when from pyspark.sql.functions import * from awsglue.utils import getResolvedOptions from pyspark.sql.types import * from datetime import datetime, date import boto3 from functools import reduce from pyspark.sql import Row import uuid from faker import Faker except Exception as e: print("Modules are missing : {} ".format(e)) spark = (SparkSession.builder.config('spark.serializer', 'org.apache.spark.serializer.KryoSerializer') \ .config('spark.sql.hive.convertMetastoreParquet', 'false') \ .config('spark.sql.catalog.spark_catalog', 'org.apache.spark.sql.hudi.catalog.HoodieCatalog') \ .config('spark.sql.extensions', 'org.apache.spark.sql.hudi.HoodieSparkSessionExtension') \ .config('spark.sql.legacy.pathOptionBehavior.enabled', 'true').getOrCreate()) sc = spark.sparkContext glueContext = GlueContext(sc) job = Job(glueContext) logger = glueContext.get_logger() # =================================INSERTING DATA ===================================== global faker faker = Faker() class DataGenerator(object): @staticmethod def get_data(): return [ ( uuid.uuid4().__str__(), faker.name(), faker.random_element(elements=('IT', 'HR', 'Sales', 'Marketing')), faker.random_element(elements=('CA', 'NY', 'TX', 'FL', 'IL', 'RJ')), str(faker.random_int(min=10000, max=150000)), str(faker.random_int(min=18, max=60)), str(faker.random_int(min=0, max=100000)), str(faker.unix_time()), faker.email(), faker.credit_card_number(card_type='amex'), ) for x in range(100) ] data = DataGenerator.get_data() columns = ["emp_id", "employee_name", "department", "state", "salary", "age", "bonus", "ts", "email", "credit_card"] spark_df = spark.createDataFrame(data=data, schema=columns) # ============================== Settings ======================================= db_name = "hudidb" table_name = "employees" recordkey = 'emp_id' precombine = "ts" PARTITION_FIELD = 'state' path = "s3://hudi-demos-emr-serverless-project-soumil/tmp1/" method = 'upsert' table_type = "MERGE_ON_READ" # ==================================================================================== hudi_part_write_config = { 'className': 'org.apache.hudi', 'hoodie.table.name': table_name, 'hoodie.datasource.write.table.type': table_type, 'hoodie.datasource.write.operation': method, 'hoodie.datasource.write.recordkey.field': recordkey, 'hoodie.datasource.write.precombine.field': precombine, 'hoodie.datasource.hive_sync.mode': 'hms', 'hoodie.datasource.hive_sync.enable': 'true', 'hoodie.datasource.hive_sync.use_jdbc': 'false', 'hoodie.datasource.hive_sync.support_timestamp': 'false', 'hoodie.datasource.hive_sync.database': db_name, 'hoodie.datasource.hive_sync.table': table_name, } spark_df.write.format("hudi").options(**hudi_part_write_config).mode("append").save(path) # ================================================================ # Adding NEW COLUMN # ================================================================ class DataGenerator(object): @staticmethod def get_data(): return [ ( uuid.uuid4().__str__(), faker.name(), faker.random_element(elements=('IT', 'HR', 'Sales', 'Marketing')), faker.random_element(elements=('CA', 'NY', 'TX', 'FL', 'IL', 'RJ')), str(faker.random_int(min=10000, max=150000)), str(faker.random_int(min=18, max=60)), str(faker.random_int(min=0, max=100000)), str(faker.unix_time()), faker.email(), faker.credit_card_number(card_type='amex'), faker.date().__str__() ) for x in range(100) ] data = DataGenerator.get_data() columns = ["emp_id", "employee_name", "department", "state", "salary", "age", "bonus", "ts", "email", "credit_card", "new_date_col"] spark_df = spark.createDataFrame(data=data, schema=columns) spark_df.write.format("hudi").options(**hudi_part_write_config).mode("append").save(path) try: print("Try1") table_name_test = f"{table_name}_ro" query = f"alter table {db_name}.{table_name_test} drop column credit_card" spark.sql(query) except Exception as e: print("ERR1", e) try: print("Try2") table_name_test = f"{table_name}_rt" query = f"alter table {db_name}.{table_name_test} drop column credit_card" spark.sql(query) except Exception as e: print("ERR2", e) ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
