Rule of Thumb for Estimating Concurrent DB Connections on a 24-Core Machine (Single Thread Each) The number of concurrent database connections a 24-core machine can handle depends on various factors, including: Hypothetical Calculation Based on CPU A single-threaded, single-core system can typically handle 2-10 concurrent active queries (depending on execution time and parallelism). For a…
In an Oracle Exadata environment, cell node storage disks are presented to compute nodes as ASM disks, and this mapping occurs through the Oracle ASM (Automatic Storage Management) and Exadata Storage Server software (CellCLI). Here’s a detailed explanation of how the cell node storage disks are mapped to the compute nodes: 1. Cell Node Storage:…
Directory Structure: root-folder/ config-folder/ json-file.config class-folder/ classfile.py tests/ pytest-file1.py json-file.config: { “setting1”: “value1”, “setting2”: “value2” } Now, Here I need to access json-file.config in my class file. I do not want to use dbutil, how can i access it and read it from json-file.config in my class file?? classfile.py import os import json class myclass:…
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I have following directory structure. root-folder – config-folder json-file.config – class-folder classfile.py – tests pytest-file1.py Now, I need to use a class named myclass from classfile.py in my test/pytestfile1.py. How can I import that class in my pytest file?? To import the myclass from classfile.py into your pytest-file1.py, you can use a relative import assuming…
In this guide, I’ll walk you through moving SQL profiles using a staging table. SQL profiles help databases optimize query execution plans. Step#1 Create the Staging Table First, create a staging table to hold SQL profiles that need to be transferred. SQL> exec DBMS_SQLTUNE.CREATE_STGTAB_SQLPROF(table_name => ‘SQL_STG_TAB’, schema_name => ‘SYS’); This will create a table SQL_STG_TAB…
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When dealing with Oracle 19c Real Application Clusters (RAC), the process of capturing a workload from a source Oracle 19c RAC database and replaying it on a target Oracle 19c RAC database using HammerDB involves some additional considerations. Below are the revised steps: Capture and Replay Workload from Source to Target Oracle 19c RAC Download…
from pyspark.sql.functions import col, lit# File location and typefile_location = “/FileStore/tables/sales_data_part1.csv”file_type = “csv”# CSV optionsinfer_schema = “false”first_row_is_header = “true”delimiter = “,”# The applied options are for CSV files. For other file types, these will # be ignored.df = spark.read.format(file_type) .option(“inferSchema”, infer_schema) .option(“header”, first_row_is_header) .option(“sep”, delimiter) .load(file_location)display(df)# Adding new column with and with default values. #…
# Databricks notebook source %sqlcreate database if not exists abcdb %sqluse abcdb %sqlcreate table student (id int , name string) %sqlinsert into studentselect 1 as id, ‘user1’ as name %sqlselect * from student spark.sql(“create database if not exists xyzdb”)spark.sql(“use xyzdb”) # Use three double quotes (“””) if SQL…
from pyspark.sql.functions import col # File location and type file_location = “/FileStore/tables/sales_data_part1.csv” file_type = “csv” # CSV options infer_schema = “false” first_row_is_header = “true” delimiter = “,” # The applied options are for CSV files. For other file types, these will be ignored. df = spark.read.format(file_type) .option(“inferSchema”, infer_schema) .option(“header”, first_row_is_header) .option(“sep”,…
# Databricks notebook source import pandas as pd # preapre dataframe df_h=pd.read_csv(“https://people.sc.fsu.edu/~jburkardt/data/csv/zillow.csv”) #Print dataframe df_h #define custom columns columns = [“Srno”, “SQFT”, “BR”, “Baths”, “Zipcode”, “YearBuilt”, “ListPrice”] df_h=pd.read_csv(“https://people.sc.fsu.edu/~jburkardt/data/csv/zillow.csv”, header=None, names=columns) #Print dataframe df_h # show top 10 rows df_h.head(10) # show last 10 rows df_h.tail(10) #Print dataframe df_h #Drop non-needed columns, column names are case…
