spark-dummy-tools 0.3.0

spark_dummy_tools

spark_dummy_tools

spark_dummy_tools is a Python library that implements for dummy table

Installation

The code is packaged for PyPI, so that the installation consists in running:

pip install spark-dummy-tools --user 

Usage

wrapper take Dummy

from spark_dummy_tools import generated_dummy_table_artifactory
from spark_dummy_tools import generated_dummy_table_datum
import spark_dataframe_tools


Generated Dummy Table Datum
============================================================
path = "fields_pe_datum2.csv"
table_name = "t_kctk_collateralization_atrb"
storage_zone = "master"
sample_parquet = 10
columns_integer_default={}
columns_date_default={"gf_cutoff_date":"2026-01-01"}
columns_string_default={}
columns_decimal_default={"other_concepts_amount":"500.00"}

generated_dummy_table_datum(spark=spark,
                            path=path,
                            table_name=table_name,
                            storage_zone=storage_zone,
                            sample_parquet=sample_parquet,
                            partition_colum=["gf_cutoff_date"],
                            columns_integer_default=columns_integer_default,
                            columns_date_default=columns_date_default,
                            columns_string_default=columns_string_default,
                            columns_decimal_default=columns_decimal_default
                           )
                       



Generated Dummy Table Artifactory
============================================================
path = "lclsupplierspurchases.output.schema"
sample_parquet = 10
columns_integer_default={}
columns_date_default={"gf_cutoff_date":"2026-01-01"}
columns_string_default={}
columns_decimal_default={"other_concepts_amount":"500.00"}


generated_dummy_table_artifactory(spark=spark,
                                  path=path,
                                  sample_parquet=sample_parquet,
                                  columns_integer_default=columns_integer_default,
                                  columns_date_default=columns_date_default,
                                  columns_string_default=columns_string_default,
                                  columns_decimal_default=columns_decimal_default
                                 )










import os, sys
is_windows = sys.platform.startswith('win')
path_directory = os.path.join("DIRECTORY_DUMMY", table_name)
if is_windows:
    path_directory = path_directory.replace("\\", "/")
    

df =  spark.read.parquet(path_directory)
df.show2(10)
  

License

Apache License 2.0.

New features v1.0

BugFix

• choco install visualcpp-build-tools

Reference

• Jonathan Quiza github.
• Jonathan Quiza RumiMLSpark.
• Jonathan Quiza linkedin.