azure-data-lake

问题 I'm trying to write the output of batch scoring into datalake: parallel_step_name = "batchscoring-" + datetime.now().strftime("%Y%m%d%H%M") output_dir = PipelineData(name="scores", datastore=def_ADL_store, output_mode="upload", output_path_on_compute="path in data lake") parallel_run_config = ParallelRunConfig( environment=curated_environment, entry_script="use_model.py", source_directory="./", output_action="append_row", mini_batch_size="20", error_threshold=1, compute_target=compute_target,

问题 I am trying to get the last modification time of each file present in azure data lake. files = dbutils.fs.ls('/mnt/blob') for fi in files: print(fi) Output:-FileInfo(path='dbfs:/mnt/blob/rule_sheet_recon.xlsx', name='rule_sheet_recon.xlsx', size=10843) Here i am unable to get the last modification time of the files. Is there any way to get that property. I tries this below shell command to see the properties,but unable to store it in python object. %sh ls -ls /dbfs/mnt/blob/ output:- total 0

问题 I have imported an excel file into a pandas dataframe and have completed the data exploration and cleaning process. I now want to write the cleaned dataframe to csv file back to Azure DataLake, without saving it first as a local file. I am using pandas 3. My code looks like this: token = lib.auth(tenant_id = '', client_secret ='', client_id = '') adl = core.AzureDLFileSystem(token, store_name) with adl.open(path='Raw/Gold/Myfile.csv', mode='wb') as f: **in_xls.to_csv(f, encoding='utf-8')** f

问题 I have imported an excel file into a pandas dataframe and have completed the data exploration and cleaning process. I now want to write the cleaned dataframe to csv file back to Azure DataLake, without saving it first as a local file. I am using pandas 3. My code looks like this: token = lib.auth(tenant_id = '', client_secret ='', client_id = '') adl = core.AzureDLFileSystem(token, store_name) with adl.open(path='Raw/Gold/Myfile.csv', mode='wb') as f: **in_xls.to_csv(f, encoding='utf-8')** f

问题 I have imported an excel file into a pandas dataframe and have completed the data exploration and cleaning process. I now want to write the cleaned dataframe to csv file back to Azure DataLake, without saving it first as a local file. I am using pandas 3. My code looks like this: token = lib.auth(tenant_id = '', client_secret ='', client_id = '') adl = core.AzureDLFileSystem(token, store_name) with adl.open(path='Raw/Gold/Myfile.csv', mode='wb') as f: **in_xls.to_csv(f, encoding='utf-8')** f

来源： https://stackoverflow.com/questions/57765991/how-to-run-python-egg-present-in-azure-databricks-from-azure-data-factory

来源： https://stackoverflow.com/questions/57765991/how-to-run-python-egg-present-in-azure-databricks-from-azure-data-factory

来源： https://stackoverflow.com/questions/57765991/how-to-run-python-egg-present-in-azure-databricks-from-azure-data-factory

来源： https://stackoverflow.com/questions/63207259/azure-datalake-analytics-u-sql-with-azure-datalake-storage-gen-2

来源： https://stackoverflow.com/questions/63207259/azure-datalake-analytics-u-sql-with-azure-datalake-storage-gen-2