DronaBlog

Monday, December 27, 2021

What is Cold and Hot virtual warehouses ?

                            The virtual warehouse in snowflake goes through various states. The states are cold warehouse, warm warehouse, and Hot warehouse. In this article, we will learn about what does each state of virtual warehouses in snowflake. We will also see what impact of states of virtual warehouses on query performance.

A) What is a virtual warehouse in snowflake?

                            The virtual warehouse in snowflake is a cluster of computing resources that are used to perform activities such as DML operations and SQL execution. The compute resources consist of temporary storage, memory, and CPU. The majority of expenses occur due to the use of a virtual warehouse or compute layer.





B) What are the states of the virtual warehouse in snowflake?

                             The virtual warehouses go through various states and these are -

                            a) Cold virtual warehouse 

                            b) Warm virtual warehouse 

                            c) Hot virtual warehouse 

                      In the next section, we will more about all these states of the virtual warehouse.

C) Cold virtual warehouse :

                             Starting a new virtual warehouse without using local disk cashing and executing the query is called a cold virtual warehouse. When our virtual warehouse is suspended or not active and if we run the query then it will start a new instance of the virtual warehouse.

D) Warm virtual warehouse : 

                             It is the state of the virtual warehouse during which the virtual warehouse is active and running for a while and processed queries. Assume that, the virtual warehouse is in a warm state and we disable the result cache and execute the query then it will use local disk caching. This caching is called warm caching.





E) Hot virtual warehouse :

                            The hot virtual warehouse is a state of virtual warehouse during which the virtual warehouse is active and running for a while and processed queries. However, in this case, the result cache is on. If we execute the query in this state, the query result is returned from the result cache. This is the most efficient operation.

F) Impact of virtual warehouse state on query performance 

                   1) Cold warehouse 

                                The query takes longer than a warm and hot virtual warehouse. It uses a remote disk. Local disk cache is not used. Result cache is not used.

                   2) Warm warehouse 

                               The query takes lesser than a cold warehouse but more than a hot virtual warehouse. It does not use a remote disk, however, it uses a local disk. It does not use result cache.

                  3) Hot virtual warehouse 

                               The query takes lesser time for execution than a cold virtual warehouse and a warm virtual warehouse. It does not use both remote disk and local disk cache. The result is returned using the result cache. from the cloud services layer. It is the most efficient way of getting the result of the query.


                         Learn more about snowflake here -



Thursday, December 23, 2021

Snowflake Interview Questions and Answers - part II

                      This is the second part of the series of snowflake interview questions and answers. For the first part i.e Snowflake interview questions and answers - part I click here .




Q1. What are the types of data warehouses? What type of snowflake data warehouse is it? 

                       Before understanding the types of data warehouses, we need to know what is a data warehouse? A data warehouse is a central data repository used for data analyses and reporting .

                       Following are the types of data warehouses

                  a) Enterprise Data Warehouse (EDW) which is a centralized warehouse used for decision making across enterprises. EDW is used for tactical and strategic decision purposes.

                 b) Operational Data Store (ODS) which is a centralized database that is the complementary element to EDW and often acts as a source to EDW, ODS gets refreshed in real-time and used for operational reporting and decision making.

                 c) Data Mart is a subset of a data warehouse and is normally used by a specific team or business line.

                    Snowflake is an analytic data warehouse i.e can be used as Enterprise Data Warehouse and it is implemented as a software As A service i.e SaaS service.






Q2. Is it possible to use data from the local system to load in Snowflake?

                   No, we can not load from the local system we need to use Amazon S3 bucket or Microsoft Azure BLOB, or Google cloud storage.

Q3. What are the important features of Snowflake? 

                  The listed below are the features of the snowflake -

                1. Database and object closing

                2. External Table 

                3. Geospatial data support 

                4. XML support

               5. Cashing

               6. Search optimization services

               7. Integration with Hive meta store 

               8. Data protection and security 

               9. Time Travel

             10. Data sharing

Q4. Can we use an external database such as Oracle or  DB2 for Snowflake storage layer ?

                     No, we can not use an external database for snowflake storage layer snowflake comes with an inbuilt database which is built on SQL database. It is a columnar stored relational database. The snowflake database works well with Tableau, Extel, and many other tools. Snowflake database provides all the services which come with SQL database such as role-based security, query tool, multi-statement transactions, etc.





Q5. What are the cashing areas in snowflake architecture? 

                     The data fetched from the storage layer is cashed at two locations  1) Compute layer 2) Cloud services layer 

                     If cloud services layer cashing is disabled then compute layer cashing is used


                  

               Learn more about snowflake here 



     

       

                               

Friday, December 10, 2021

Snowflake Interview Questions and Answers - Part I

                 This is the first article on a series of Interview Questions and their answers on Snowflake. Through these questions and answers we will learn more about Snowflake so let's start.




Q 1 . What is the architecture of Snowflake?

                  Snowflake architecture is a hybrid architecture of shard-disk and shared-nothing database architectures. As like shared-nothing architecture, snowflake processes queries using massively processing compute clusters where each node store some portion of data locally. on other hand, as like shard-disk architecture, snowflake uses a central repository for data & it is accessible from compute nodes.

                 Snowflake architecture has three layers i.e database storage to store data, Query processing or compute layer for processing queries and the third layer is cloud services which provide services such as security, metadata, and optimizer.








Q2. What are cloud platforms are supported by Snowflake?

                  Snowflake supports the following cloud platforms -

                 1. Amazon Web Services (AWS)

                 2. Google cloud platform (GCP)

                 3. Microsoft Azure ( Azure)


Q3. Do you consider snowflake as an ETL tool? 

                Yes, snowflake can be considered an ETL tool because it performs extract, transform, and loads operations like other ETL tools.

                a) Extract Process: With help of this process, snowflake extracts data from the source and creates data files. these data files support various data formats like CSV, XML, JSON, etc.

                b) Transform Process: We can write a custom transform process in snowflake to pull data from the source and apply some transformations for cleansing and standardization and then load the data.

               c) Load Process: With the load process, we can load data to the internal or external stage. we can use Microsoft  Azure Blob, Amazon S3 bucket or snowflake managed location for staging data. The data is copied to snowflake storage using the COPY INTO command.






Q4. What are the different Editions of Snowflake?

               Here is list of snowflake Editions 

             a) Standard Edition 

             b) Enterprise Edition 

             c) Business -critical Edition

             d) Virtual Private snowflake 


Q5. What kind of SQL does snowflake use?  

             Snowflake uses ANSI SQL which is a common standard version of SQL.


     

         

      

            


        Learn more about snowflake here 


Monday, December 6, 2021

What are the phases in BES External call in Informatica MDM ?

                 Are you looking for the details about various phases in BES External calls? Are you also interested in knowing what are categories under which these phases come? If so, then you reached the right place. In this article, we will learn about BES  External calls and their phases.

A) What BES External calls?

                BES External calls are the web service configured in the provisioning tool in order to achieve customization in Entity 360 or Customer 360 application. we need to develop a custom web service and deploy it on the application server. Once it is deployed, we can register the endpoint URL in the provisioning tool in Informatica MDM.





B) Categories of phases of BES External calls? 

                 The phases of BES External calls are categorized as -

                      a) Read calls

                     b) Write calls 

                     c) Merge calls  

               a)  Read calls: This category is used for read and search operations.

              b)  Write calls: This category uses write co for insert, update and delete operations.

              c)  Merge calls: This category uses preview merge co which is designed for merge-operations.

C)  Phases of External calls 

                   Let's understand detailed phases for the above categories 

              i) Read call phases : 

                        The phases for read calls are

                      * Read Co.Before Everything 

                      * Read Co.After Everything 

                      * Read view.Before Everything

                      * Read view.After Everything






             ii) Write call Phases

                      * Write Co.Before Everything

                      * Write Co.Before Validate

                      * Write Co. After Validate

                      * Write Co.After Everything  

                      * Writeview. Before Everything 

                      * Writeview. Before Vadidate

                      * Writeview. After Vadidate

                      * Writeview. After Everything


               iii) Merge call phases

                      * Perview Merge Co. Before Everything

                      * Preview Merge Co.After Everything

                      * Merge Co. Before Everything

                      * Merge Co. After Everything


                 Learn more about Informatica here 



            

                   

                

Dynatrace : An Overview

  Dynatrace, a leading provider of software intelligence, offers a powerful platform designed to monitor, analyze, and optimize the performa...