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This article was published as a part of the Data Science Blogathon.Introduction
Microsoft’s Power BI is one of its rapidly growing corporate analytics services. This self-service business intelligence tool is the latest and greatest in the data-driven industry. It eased the workaround for attaining data from several sources and consolidating it into one management tool.
Many of the world’s leading companies use Microsoft Power BI to gain superior business insights. In addition, Microsoft Power BI has been positioned in Gartner’s Magic Quadrant for the fifteenth year as premier analytics and business intelligence platform. In the next years, Power BI will continue to be an industry leader in scope. If you enjoy working with data, visualizations, gaining insights, etc., obtaining a Power BI certification could stand you apart in the job market.What is Power BI?
Power BI is the current buzzword in the data-driven IT business. Numerous power BI potentials exist across several editions. With enough understanding of the equipment, it is simple to seize chances as a:
Power BI data analyst
Power BI consultant
Power BI software engineer
Power BI project manager
Power BI developer
SQL Server Power BI developerInterview Questions 1. What are Power BI’s most important elements?
Power Pivot: It is used for data modeling that employs DAX (Data Analysis Expression) functions. Here, we can build relationships between many tables and get values that may be shown in pivot tables.
Power View: The Power View presents data intelligibly and gets metadata for data analysis. The views are interactive, and slicers and filters are available for manipulating the data.
Power BI Desktop: Power Desktop is a Power Query, Power View, and Power Pivot integration tool. It facilitates the creation of complex queries, data models, reports, and dashboards, along with developing BI skills for data analysis.
The Power BI Mobile App is available on Android, iOS, and even Windows operating systems. The App has an interactive dashboard display that can be shared.
Power BI Map: It displays geospatial visualization of the data in three-dimensional mode. The data may be highlighted based on geographical location, a continent, state, city, or street address.
Power BI Q&A: It is used to deliver responses to user-posed inquiries. It is compatible with Power View and may be replied with diagrams using Power Q&A.
(Source: InterviewBit)2. What is Microsoft’s Power BI Gateway?
Power BI Gateway is a software program to access on-premises network data from the cloud. Gateways are gatekeepers for data sources located on-premises. Requests for access to on-premises data from cloud or web-based applications are sent through the gateway. The gateway handles all connection requests and grants access depending on the user’s authentication and criteria.
Gateways do not transmit data from the source on-premises to the client platform. It just links the platform to the on-premises data source so that customers can easily access the data. Gateways have employed a link between a single or several data sources and an on-premises data source.3. What is the Dax Function used by Power BI?
Data Analysis Expression (DAX) is a formula library for data analysis and computation. This library includes calculation-performing functions, constants, and operators. DAX facilitates the optimal usage of data sets and the generation of meaningful outputs.
DAX is a functional programming language that supports conditional statements, nested functions, value references, and much more. There are either numeric (integers, decimals, etc.) or non-numerical formulae (string, binary). Every DAX formula begins with an equal sign.
DAX Syntax:Total Sales = SUM(Sales[SalesAmount])
Where ‘Total Sales’ represents ‘Measure,’ ‘SUM’ represents ‘DAX Function,’ and ‘Sales[SalesAmount]’ is the table and column reference.4. What are Microsoft’s Power BI formats?
The several Power BI formats are as follows:
Power BI Desktop – You may download and install Power BI Desktop on your computer. With templates, you may connect it to the data source, convert the data, and analyze and visualize it.
Power BI Services – Power BI Services is a cloud-based Service-as-a-Platform.
Power BI Mobile App – The Power BI Mobile App is available for iOS, Android, and Windows.5. What do you mean by the content pack in Power BI?
A content pack is a pre-assembled collection of visualizations, and Power BI reports created with your preferred service. Instead of writing a report from scratch, you would utilize a content pack when you need to start quickly.6. What visualization types does Power BI support?
Visualization is the rendering of data graphically. Using visualizations, we may generate reports and dashboards. Power BI visualizations include Bar charts, Column charts, Line charts, Area charts, Stacked area charts, Ribbon charts, Waterfall charts, Scatter charts, Pie charts, Donut charts, Treemap charts, Maps, Funnel charts, Gauge charts, Cards, KPI, Slicers, Tables, Matrix, R script visualizations, and Python visualizations, among others.7. Where does Power BI store data?
When data is imported into Power BI, it is stored primarily in Fact and Dimension tables.
Fact tables: The central table in a star design of a data warehouse, the fact tables hold non-standardized quantitative data for analysis.
Dimension tables: Dimension tables are the only additional table in the star schema used to record characteristics and dimensions that characterize entities in the fact table.8. What is Power BI’s complete functioning system?
Microsoft’s Power BI system consists mainly of three steps:
Data Integration: Data Integration begins with the extraction and integration of data from disparate data sources. After integration, the data is converted into a standardized format and stored in a staging area.
Data Processing: After the data has been compiled and merged, it must be cleansed before processing. Therefore, a few modifications and cleaning operations are done on the data to remove redundant numbers, etc., as raw data is not very valuable. The modified data is then stored in data warehouses.
Data Presentation: Now that the data has been translated and cleansed, It is shown on the Power BI desktop in the form of reports, dashboards, and scorecards. These reports may be shared with multiple corporate users through mobile apps or the web.10. What do you understand by Power BI Designer?
Power BI Designer, a powerful and flexible tool under the Power BI umbrella, allows users to build intuitive reports and dashboards easily and swiftly and to modify the visual perspectives of their data on the fly for improved analytics and well-informed decision. This designer is replete with drag-and-drop features that allow users to position content accurately where they want it on the report canvas systematically.
The following are some of Power BI’s limitations:
Complex in nature: Power BI has a fairly sophisticated design. Users must comprehensively understand Power BI before they can begin using it.
Problems with Large Data: Power BI cannot analyze large datasets and may stall out when trying to do so. It is unable to handle files larger than 1 GB.
Limited Sharing of Data: Users who are on the same domain or whose email addresses are designated in Office 365 are the only ones who may get the files you share.
Limited Source of Data: Power BI allows real-time connectivity with a small number of data sources.Conclusion
Microsoft Power BI is the focus of this article. An analytics system developed by Microsoft, Power BI facilitates the conversion of diverse data sources into relevant and interactive insights. A fast-growing corporate analytics service from the company. Some key takeaways from the article are:
What are Power BI and its important elements?
A complete functioning system of Power BI.
Where does Microsoft’s Power BI store data?
In addition to Power BI Gateway, Power BI Designer, and Power BI Formats, other subjects are also covered.
I hope this Microsoft’s Power BI Interview Questions and Answers help you prepare for your upcoming interviews. Wishing you the best!
The media shown in this article is not owned by Analytics Vidhya and is used at the Author’s discretion.
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Power BI error in loading a previous table: Fix it with our steps
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If you have a Power BI report connected to Data in an Excel file in the Power BI Service or Desktop client, you can refresh the data using the refresh button to update the table. However, some users have reported Power bi error in loading a previous table in their Power BI dashboard.
Follow the steps listed in this article to fix load was canceled by an error in loading a previous table Power BI error.How to fix the Power BI error in loading a previous table 1. Delete and Recreate Query
Start with saving the affected query M code.
Next, delete the affected query from the dashboard.
Now recreate the query using the previously saved M Code.
Try to refresh the database again and check if the error in loading a previous table occurs again.
If the issue persists, check if any of the queries have incorrect DAX formula.
If you find any incorrect DAX formula in any of the queries, delete the formula.
Load the query again and check for any improvements.
The error can occur due to incorrect syntax that otherwise will skip your attention.
Most users didn’t know that Microsoft Excel uses AI to turn pictures of tables into editable tables. Learn about it here.2. Change Power BI Options
From the Power BI Dashboard, go to Settings.
Uncheck “Enable parallel loading of tables” option.
Now try to load the query and check if the error is resolved.
This error can also occur if the Access app cannot handle Parallel loading that we disabled earlier resulting in the error.
If the issue persists, check if you have deleted or edited a column in a referred table.3. Undo the Changes
If you are getting the error after you modified the Excel sheet related to your Power BI service, you can fix it by reverting the changes.
Simply undo the changes you made to the Excel file.
Make sure you revert the changes made to the Excel sheet for each query and update the tables manually to resolve the error.
If the issue persists, try with Direct Query instead of Import Query when you get the data.
Another reason why the error can occur is if you have changed the name for any of the tables in Excel and not in PBix. To fix this open the Advanced editor and rename the tables to match the names in Excel file.
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Today, I’m going to do a quick and easy tutorial on how to calculate one of the most commonly used metrics, especially if you’re dealing with sales, revenues, or transactions. We’ll calculate the percentage margin. I’m going to use profit margin as an example here, but this technique doesn’t have to be always related to profits; it could be any sort of margin. You can watch the full video of this tutorial at the bottom of this blog.
Let’s jump to the model first. We want to make sure that it has been set up in an optimized way. I know that Microsoft formats the model using a star schema. Personally, I’m not very fond of it. Instead, I use the waterfall technique, which is sometimes called the snowflake technique.
This technique is where the filters flow down to your fact table from your lookup table.
Let’s have a quick look at our Sales table. As you can see, there’s no way to create the percent profit margin because there are no profit numbers in the table.
When they’re starting out with Power BI, most users will create a calculated column, calculate the profits, and then from there, work out the profit margin.
The great thing about Power BI is that you can do all of these calculations inside of measures.
I’ve created a simple measure called Total Sales which sums up the Total Revenue column. Even if you’re dealing with something totally different like HR data or marketing data, the techniques I discuss are reusable across any industry and business function.
The examples I will show use the measure branching technique, where we start with our core measures and then branch out into other measures like margins.
With measure branching, we start off with a core measure like Total Sales, and then create another measure called Total Costs. In this measure, I’ll use SUMX which enables me to do calculations at every single row of a table. It will iterate through every single row of the table I specify, which in this case is the Sales table. For every row, I will multiply Quantity by Total Unit Costs.
Remember that in the Sales table that we just looked at, there was no actual Total Costs column. There were only these two columns. This is why I needed to do multiplication at every row, and then sum up the results. This is what SUMX and all the iterating functions do.
We now have Total Sales and Total Costs in our table.
I can create another really simple measure called Total Profits. This is where measure branching comes in. I’m going to simply branch out again and find out the difference between Total Sales and Total Costs.
I’ve also placed the Total Profits in my table.
To calculate the percentage margin, I will create another measure. I’m going to use a function called DIVIDE to divide the Total Profits by the Total Sales, and I’m going to put an alternative result of zero.
We’ll also turn this into a percentage format.
We can now see the percentage margin.
Some of you might ask why we didn’t do this using just one formula. My recommendation is to branch out slowly and start from the simplest measures before you create the more complicated ones. Think about how easy every single measure was that we worked through when we build it step by step. It’s easier to audit when you’re able to break things out in a table and be able to look at the results and double-check the numbers.
Once I turn this table into a visual, it’s a bit busy and all the data is similar when you look at the customers.
If you want your visualization to stand out, the best way to showcase this is with conditional formatting, especially when you have a lot of data points that are quite similar.
You can change the background color and use two contrasting colors. You can go from light to dark blue.
Another thing you can do is change what you showcase in the axis and start at 30%.
You can now see more variability in the visualization. Obviously, you just need to make sure that your consumers know what they’re looking at.
Most of you who are just starting out with Power BI have probably overlooked this particular function. I certainly did when I first started out using Power BI and writing DAX measures.
It’s quite a complex function to understand and actually implement in Power BI. But over time, I’ve discovered how great it is in several scenarios and demos I’ve worked through. I now have a clear understanding of how and when to use it in different ways. That’s what I want to share with you in this tutorial.
One of the best times to incorporate the use of the CALCULATETABLE DAX function is when you’re trying to analyze your churn analytics.
Churn analytics involves the evaluation of a company’s customer loss rate. Finding out this data using Power BI can help a lot in terms of assessing your products. Through this way, you can speed up your marketing efforts to reduce customer loss.
The table above shows a comparison of new and total customers for a specific month and year. It involves the data of new, lost, and total customers.
The key to extracting these important insights is through the use of the CALCULATETABLE DAX function.
Firstly, I’ll show you the formula to calculate new customers using CALCULATETABLE.
Here, we need to compare the current customer set from a customer set of a prior period. I only consider customers as new, if they have purchased now but haven’t done so in the past 90 days.
To be able to find that insight, this is where I integrated the CALCULATETABLE function. Take note that I used this together with other table functions, just like the EXCEPT function.
The EXCEPT function evaluates two tables and returns the customers that are in the first table, but not on the second one. Next, I wrapped it inside the COUNTROWS function to really work out the needed calculation.
Looking back to the main point. The CALCULATETABLE function enables us to open a window in any particular context. In my example, it looks back 90 days to find a customer set.
Since we don’t want to look at the customers in the current context, but look at the customers over the previous 90 days, we now use the FILTER function.
Then, I’ve placed it inside another table function and do some follow-up evaluations.
To sum up, the perfect way to use CALCULATETABLE is to change the context of a table evaluation. That’s generally how you should use it. But then, you can also incorporate other formulas that you can use to compare tables like EXCEPT and INTERSECT.
Take a look at this formula for finding out lost customers.
I have actually discussed the full logic of this formula in another blog. But then again, we’re just doing a similar calculation here for lost customers.
If you look at the formulas for CustomersPurchased and PriorCustomers, we’re using CALCULATETABLE.
Furthermore, you can still find the EXCEPT function. But this time, it compares the tables of CustomersPurchased and PriorCustomers.
If you use Power BI soon, you’ll understand that this is an intensive analysis. Moreover, we can make the formulas more intuitive especially when you use variables as well.
Just think about what you put inside the first parameter in CALCULATETABLE. It’s usually a table function, and then you change the context of that table evaluation. From there, you can put it inside another table function and see how things evaluate from there.
I know CALCULATETABLE is a bit hard to understand if you’re just starting out. But that’s the main reason why I created this tutorial for you.
By reviewing it in this way, I believe you’ll have a better understanding of how you can utilize the CALCULATETABLE DAX function yourself in your own reports and models.
Don’t forget to subscribe to Enterprise DNA TV to get plenty of other content.
Good luck with learning this one.
In this tutorial, we’ll discuss a custom visual called Bullet charts. They’re mainly used for measuring performance against target or previous years.
Bullet charts are useful visuals for comparing employee performance, shipment targets, sales targets, production targets, and many more.
This is a sample bullet chart that I have created. We’ll discuss how I created this bullet chart and the things that we can do in this particular custom visual.
This is the data that we’ll be using in this example. It contains the player names, goals scored, target, and goals for last year. Later in this tutorial, we’ll create measures for the calculated columns.
Search for “Bullet”, then add the Bullet Chart by OKViz.
This is the one I prefer because it also shows the negative values on the other side if we have it in our data.
Let’s add this visual on our report page and resize it.
Then, add the Player for the Category field and the Goals Scored measure for the Value field.
We should get this output. As you can see, we currently have bandings in our bullet chart. These are represented by the different hues of gray.
Let’s now drag the Target measure on the Targets field.
It will then add target markers on our output.
In the General section of the Formatting tab, we can also change the orientation of our visual to vertical if we want to.
By default, if we resize this visual on our report page, the bars will also be resized automatically.
If we don’t want that to happen, we can just set the minimum or maximum height of the bars.
After setting the maximum height of the bars, it will then look like this.
This part of the visual is the categories. If we want to, we can turn them off by disabling the Category.
For this example, it’s better if we leave this turned on.
The Value axis is the X-axis of the visual. We can also turn off this one.
But for this example, let’s just leave it on.
Another feature that would be useful is the Data labels.
It will then show these labels which are the scores of our categories (the players).
Another cool thing about this visual is the conditional formatting. If we’ll just use a bar chart here, we won’t be able to conditionally format each one of the categories.
As you can see from the image, only one target was set for all the individual players.
However, in our dataset, there are different targets for each of the individual players.
So, using a bar chart won’t create the visual that we want. That’s the reason why we are using a bullet chart in this particular example.
As you can see, we can now set the if condition.
Let’s assign a red color for this condition so we can see which players are behind their target scores.
Obviously, these 3 players are behind their target scores.
We can also change the color of the target markers. For this example, we’ll just use black.
We can change the shape of the target marker as well. For this example, let’s stick to the Line shape because it looks better than the other shapes.
In this visual, you can see the gray parts behind the bars. These are called Bandings.
We can define static or dynamic bandings. For dynamic bandings, we can do that by creating calculated measures. We’ll be doing that after learning how to define static bandings.
For static bandings, we can set them here.
Currently, there are 5 States where we can set a value for each of them.
We can define the State by an Absolute value or Percentage. In this instance, let’s use an Absolute value.
For State 1, let’s set the value to 60 and change the color to a darker gray.
As you can see, the banding changed on our visual.
Let’s then set the value and color for the other states. Make sure that the succeeding value you’ll be using is always higher than the previous state values.
As you can see, we also used a lighter gray color for every succeeding state.
Now, the output should look like this.
So, that’s how we can set a static banding.
For the dynamic bandings, we can place the measures in the States field. This will automatically override the static bandings that we defined previously.
Let’s now display the legends and set their position.
It should then look like this.
Let’s also turn off the Title and Background.
Let’s define a new column as State 1 and set 60% for the target goal. To get the percentage value of the first state, just multiply the Target value to .60. This basically means that if a player achieved only 60% of the target goal, they will be kicked from the team.
For State 2, let’s use 70% and multiply the Target value to .70. This time, if the player reaches 70% of their target goal, they must be retained on the team.
Let’s add another column for State 3. For this one, let’s set 80% for the target goal and multiply it by .80. If the players achieved 80% of the target goal, their contract price will be raised.
Then, for State 4, let’s set the goal to 100%. If the player achieves 100% of their target goal, we must do anything to retain these players.
For State 5, we’ll set the maximum value from either the Goals Scored or Target value. So, let’s define this with an if conditional statement wherein if the Goals Scored is greater than the Target, then we’ll get the Goals Scored. Else, we’ll get the Target value.
Before we can use these calculated column measures, we need to change their format to Whole number. Make sure to change each one of them.
Let’s then add the first state on the States field.
As you can see, the first band has changed.
Let’s now add the other states on the States field.
The output should then look like this.
We now have the dynamic bandings on our custom bullet chart. With this, we can easily see who the best players and the worst players are.
The other thing that we can do with this visual is to use the Show % change over option. We can use this to compare how far a certain individual or player exceeded their target goal. For this example, let’s use the Closest achieved target.
On our visual, we’ll see that Christiano exceeded 9% of his target goal, and Salah exceeded 6% of his target goal.
We can also use the Comparison value. However, we need to add an additional measure for comparison if we will use this.
For instance, let’s add the previous year target goals (Goals LY) on the Comparison value field. ‘
As you can see, the Comparison value works now. We can finally see that Christiano already achieved 41% of his target goal last year while Salah got 31%.
Let’s remove the Comparison value for this example.
Let’s keep using the Closest achieved target instead.
The last thing that we should do is the legends for the bandings. This is because we don’t really know what these bandings mean in our visual.
To create the legend for our bandings, let’s add a 100% Stacked bar chart visual.
Then, let’s place our dynamic states on the Values field.
After that, turn off the Title.
Turn off the Title under the X and Y axis.
Then, turn off the X and Y axis as well.
State 3 wasn’t added, and State 2 was added twice. So, let’s remove the second State 2 and add State 3 instead.
Let’s change the colors of the states and use the same colors as the bandings on our bullet chart (darker gray to lighter gray).
We can also change the names of these states for the legend. For example, let’s change the first state to Kick the Players.
Let’s then change the name of the other states.
We can also create this using PowerPoint to make the legend look more appealing. If we don’t want to use PowerPoint, we can just turn off the Legend option.
Then create our label as “Kick the Players” and style it using this text box.
After that, move the text box on top of the bar chart and align it to the first bar.
Then duplicate the first text box to change the text and color that correspond to our legend bars.
We can now select the text boxes and the bar chart to group them.
Then, properly position the bullet chart and the bar chart.
To sum up, you’ve learned how to create bullet charts and customize them. You’ve also learned a new technique called Banding, which allows you to group data into chunks based on your underlying data. Static and Dynamic are the two types of bandings in Power BI.
You’ve also gained an understanding of how comparisons can be made possible in bullet charts and how they can elevate the presentation of your data.
I hope you liked this tutorial and found it useful for your data visualizations.
Until next time,
This article was published as a part of the Data Science Blogathon.Introduction
HBase is a column-oriented non-relational database management system that operates on Hadoop Distributed File System (HDFS). HBase provides a fault-tolerant manner of storing sparse data sets, which are prevalent in several big data use cases. It is ideal for real-time data processing or random read/write access to large data volumes. In contrast to relational databases like SQL, HBase doesn’t provide a structured query language like those provided by that database.
HBase is a data model that works like Google’s “big table” to make it easy to get to a lot of structured data quickly. It comprises a set of tables that store data in a key-value format. Programmers can use Hbase’s APIs in whatever programming language they want. Data in the Hadoop File System may be read and written in real time using this element of the Hadoop ecosystem.
Either directly or via HBase, data may be stored in HDFS. The data consumer uses HBase to read/access HDFS data at random. Read and write access to the Hadoop File System is provided by HBase.
Any number of columns can be added to the horizontal scalability at any moment.
A multidimensional sorted map is indexed by row key, column key, and timestamp in a distributed manner.
In the case of a system breach, an administrator can use automatic failover to automatically transition data handling to a standby system.
Built on top of the Hadoop Distributed File System, each command and Java code implements Map/Reduce internally to complete the operation.
Frequently referred to as a key-value store, column family-oriented database, or for storing versioned maps of maps.
It is basically a system for storing and retrieving data with random access.
It does not impose relationships between data elements.
It is intended to run on a cluster of commodity hardware-based computers.Interview Questions
1. What is Apache HBase’s purpose?
Apache HBase is used when random, real-time read/write access to Big Data is required. The objective of this project is to host tables with billions of rows and millions of columns on clusters of commodity hardware. Apache HBase is a distributed, versioned, non-relational, open-source database inspired by Google’s Bigtable: A Distributed Storage System for Structured Data by Chang et al. Apache HBase delivers Bigtable-like functionality on top of Hadoop and HDFS, much as Bigtable utilizes the distributed data storage provided by the Google File System.
2. What are the major elements of HBase?
Major elements of HBase are:
Zookeeper: It performs coordination work between the client and HBase Master.
HBase Master: HBase Master keeps an eye on the Region Server.
RegionServer: RegionServer is responsible for monitoring the Region.
Region: It contains both the in-memory data store (MemStore) and the Hfile.
Catalog Tables: Tables in catalogs consist of ROOT and META.
3. Examine the purpose of filters in HBase.
Filters were added to Apache HBase 0.92 to make it easier for users to access HBase through Shell or Thrift. As a result, they handle your server-side filtering requirements. There are also beautifying filters, which allow you to get more control over the data produced by filters. Here are some HBase filter examples:
Bloom Filter: A space-efficient means of determining if an HFile contains a given row or cell, it is typically used for real-time queries.
Page Filter: The Page Filter can optimize the scan of particular HRegions by accepting the page size as a parameter.
4. How does HBase handle a failed write?
In big distributed systems, failures are common, and HBase is no exception.
If the server hosting a MemStore that has not yet been drained crashes. The data in memory, but not yet persisted, are gone. HBase prevents this by writing to the WAL before the write operation is finished. Every server included in the.
5. Describe deletion in HBase. What are the three types of tombstone markers supported by HBase?
When a cell is deleted in HBase, the data is not truly removed; instead, a tombstone marker is placed, rendering the deleted cell inaccessible. HBase that has been deleted is removed during compactions.
There are three types of tombstone markers:
Version delete marker: It identifies a single version of a column for deletion.
Column delete marker: It flags for deletion of every version of a column.
Family delete marker: It flags every column in a column family for deletion.
6. How does HBase compare to Cassandra?
Cassandra and HBase are both NoSQL databases, a word that has several definitions. Typically, it indicates that SQL cannot be used to manipulate the database. Nonetheless, Cassandra has implemented CQL (Cassandra Query Language), whose syntax is evidently based on SQL.
Both are intended to manage enormous data collections. According to the HBase documentation, an HBase database should include hundreds of millions or, preferably, billions of records. If not, you should continue with a relational database management system.
Not just in terms of how data is kept but also in terms of how the data may be accessed; both are distributed databases. Clients can connect to any cluster node and have access to any data.
HBase lacks native support for secondary indexes but provides a range of methodologies that enable secondary index functionality. These are outlined in the online reference guide for HBase and the HBase community.
7. What happens when the block size of a column family in a previously populated database is altered?
When you modify the block size of a column family, the new data will occupy the new block size, but the old data will stay in the old block size. In the course of data compression, old data will adopt the new block size. As new files are flushed, their block size will change, although current data will remain accurately read. After the next major data compression, all data must be converted to the new block size.
8. Why would you use HBase?
High storage capacity system
Distributed layout to accommodate big tables
Superior functionality & Availability
HBase aims for at least millions of columns, thousands of versions, and billions of rows.
Unlike HDFS (Hadoop Distributed File System), it provides CRUD operations in random real-time.
9. What is the Hbase standalone mode?
This option can be enabled when users do not require Hbase to access the HDFS. It is basically a default mode in Hbase, and users are typically allowed to use it whenever they choose. When the user selects this option, the Hbase uses a file system rather than HDFS.
It is possible to save a significant amount of time by using this mode when doing some key activities. During this mode, you may also impose or remove various time constraints on the data.
10. Contrast HBase and Hive?
Hive can enable SQL-savvy users to perform MapReduce jobs. Since it is JDBC-compliant, it is also compatible with current SQL-based applications. Since Hive queries traverse all of the table’s contents by default, their execution may be time-consuming. Nonetheless, Hive’s partitioning function can restrict the volume of data. Partitioning enables the execution of a filter query across data stored in distinct folders and the reading of just the data that matches the query. It might be used, for instance, to only process files generated between specific dates if the file names contain the date format.
HBase operates by storing data as key/value. It provides four core operations: put for adding or updating rows, scan for retrieving a range of cells, get for returning cells for a particular row, and delete for removing rows, columns, or column variants. Versioning is provided to retrieve past data values (the history can be deleted now and then to clear space via HBase compactions). Although HBase contains tables, a schema is necessary only for tables and column families but not for individual columns, and increment/counter functionality is supported.
MapReduce tasks operate on Hive, a SQL-like engine; HBase, a NoSQL key/value database, runs on Hadoop.Conclusion
This article provides information about HBase, a column-oriented non-relational database management system, and covers a variety of topics, I hope that this information was useful and that you are now more prepared for the next interviews. Here are some of the article’s most salient points:
What is HBase, and what are its features?
HBase filters and modes are available.
HBase comparisons with Hive and Cassandra, as well as many other topics at the basic, intermediate, and tough levels.
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