WHAT IS QLIKVIEW AND ITS COMPONENTS

Qlikview does in-memory data processing, data integration and stores them. It can read data from files and relational databases. Supports creation and consumption of dynamic apps. It makes the data presentation in an interactive way.

QlikView has 3 major components:

1. QlikView Desktop: It is a development tool
2. QlikView Server: Stores QlikView applications
3. QlikView Publisher: Loads data from sources and publishes it to the clients.

• QlikView – the data access solution that enables you to analyze and use information from different data sources.
• A number of features have been added to QlikView 10 with the purpose of providing possibilities to add metadata to the QlikView document. Adding metadata remains entirely optional for the developer.
• Fields can now be tagged with system defined and custom meta-tags. A number of system tags are automatically generated for the fields of a document when the script is executed.
• In analogy to field comments it is also possible to read or set comments in source tables. The comments are shown in the Tables page of the Document Properties dialog and as hover tooltips in the Table Viewer.
• Chart expressions can be given for an explanatory text comment. These are visible and editable in the Expressions page of the Chart Properties dialog,
• The script editor has been redesigned. A number of new commands can be found in the menus, e.g. the ODBC administrator can now be opened from inside the script editor; also the 32 bit ODBC administrator can be opened from a 64 bit QlikView
• The basic idea is that QlikView at script run spawns a second process – QVConnect – that in turn connects to the data source.  Two different QVConnect files are installed in the QlikView folder: QVConnect32.exe and QVConnect64.exe. It is also possible to develop custom connect programs.
• The interpretation and transformation of data are now done in multiple threads, which speeds up the load process tremendously. This does not imply any changes to the load script, i.e. the load script is still sequential: no parallel branches can be defined.
• In previous versions, Input Fields needed to be loaded in a well-defined order for their values to be correctly associated after a reload. The Input Field values were always associated with the same record number, which caused problems if the load order changed, for example by inserting new values.
• This is a new file/stream format for high performance input to QlikView. A QVX formatted file contains metadata describing a table of data and the actual data. In contrast to the QVD format, which is proprietary and optimized for minimum transformations inside QlikView, the QVX format is public and requires a few transformations when exporting data from traditional database formats

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Author

Lianamelissa is Research Analyst at Mindmajix. A techno freak who likes to explore different technologies. Likes to follow the technology trends in market and write about them.

Microsoft Dynamics AX Interview Questions

If you're looking for Microsoft Dynamics AX Interview Questions for Experienced & Freshers, you are at right place. There are lot of opportunities from many reputed companies in the world. According to research Microsoft Dynamics AX has a market share of about 6.6%. So, You still have opportunity to move ahead in your career in Microsoft Dynamics AX. Mindmajix offers advanced Microsoft Dynamics AX Interview Questions that helps you in cracking your interview & acquire dream career.

Q. What is Microsoft Dynamics AX?
Microsoft Dynamics AX is multi-language, multi-currency, industry-specific, global ERP Product and one of the Microsoft’s Dynamics ERP Family.

Q. Difference between edit and display method
Display Indicates that the method’s return value is to be displayed on a form or a report.
The value cannot be altered in the form or report
Edit Indicates that the method’s return type is to be used to provide information for a field that is used in  in a form. The value in the field can be edited.

Q. Difference between perspectives and table collection
Perspectives can organize information for a report model in the Application Object Tree (AOT).
A perspective is a collection of tables. You use a report model to create reports.
Table collection is a collection of table, which sharing across all the virtual companies.

Q. Define IntelliMorph
IntelliMorph is the technology that controls the user interface in Microsoft Dynamics AX. The user interface is how the functionality of the application is presented or displayed to the user.
IntelliMorph controls the layout of the user interface and makes it easier to modify forms, reports, and menus.

Q. Define MorphX  
The MorphX Development Suite is the integrated development environment (IDE) in Microsoft Dynamics AX used to develop and customize both the Windows interface and the Web interface.

Q. Define X++  
X++ is the object-oriented programming language that is used in the MorphX environment.

Q. Differentiate refresh(), reread(), research(), executequery()
refresh() will not reread the record from the database.  It basically just refreshes the screen with whatever is stored in the form cache.
reread() will only re-read the CURRENT record from the DB so you should not use it to refresh the form data if you have added/removed records.  It’s often used if you change some values in the current record in some code, and commit them to the database using .update() on the table, instead of through the form datasource.  In this case .reread() will make those changes appear on the form.
research() will rerun the existing form query against the data source, therefore updating the list with new/removed records as well as updating existing ones.  This will honour any existing filters and sorting on the form.
executeQuery() is another useful one.  It should be used if you have modified the query in your code and need to refresh the form.  It’s like
research() except it takes query changes into account.

Q. Define AOT
The Application Object Tree (AOT) is a tree view of all the application objects within Microsoft Dynamics AX. The AOT contains everything you need to customize the look and functionality of a Microsoft Dynamics AX application

Q. Define AOS  
The Microsoft Dynamics AX Object Server (AOS) is the second-tier application server in the Microsoft Dynamics AX three-tier architecture.
The 3-tier environment is divided as follows:
1. First Tier – Intelligent Client
2. Second Tier – AOS
3. Third Tier – Database Server
In a 3-tier solution the database runs on a server as the third tier; the AOS handles the business logic in the second tier. The thin client is the first tier and handles the user interface and necessary program logic.

Q. Difference between temp table and container.
1. Data in containers are stored and retrieved sequentially, but a temporary table enables you to define indexes to speed up data retrieval.
2. Containers provide slower data access if you are working with many records. However, if you are working with only a few records, use a container.
3. Another important difference between temporary tables and containers is how they are used in method calls. When you pass a temporary table into a method call, it is passed by reference. Containers are passed by value. When a variable is passed by reference, only a pointer to the object is passed into the method. When a variable is passed by value, a new copy of the variable is passed into the method. If the computer has a limited amount of memory, it might start swapping memory to disk, slowing down application execution. When you pass a variable into a method, a temporary table may provide better performance than a container

Q. What is an EDT, Base Enum, how can we use array elements of an EDT?
EDT – To reuse its properties. The properties of many fields can change at one time by changing the properties on the EDT. Relations can be assigned to an edt are known as Dynamic relations.
EDT relations are Normal and Related field fixed.
Why not field fixed – field fixed works on only between two tables 1- 1 relation. And Related field fixed works on 1- many tables.so edt uses related field fixed.
BaseEnum – which is a list of literals. Enum values are represented internally as integers. you can declare up to 251 (0 to 250) literals in a single enum type. To reference an enum in X++, use the name of the enum, followed by the name of the literal, separated by two colons . ex -NoYes::No.

Q. Definition and use of Maps, how AddressMap (with methods) is used in standard AX?
Maps define X++ elements that wrap table objects at run time. With a map, you associate a map field with a field in one or more tables. This enables you to use the same field name to access fields with different names in different tables. Map methods enable to you to create or modify methods that act on the map fields.
Address map that contains an Address field. The Address map field is used to access both the Address field in the CustTable table and the ToAddress field in the CustVendTransportPointLine table

Q. What is the difference between Index and Index hint?
Adding the “index” statement to an Axapta select, it does NOT mean that this index will be used by the database. What it DOES mean is that Axapta will send an “order by” to the database. Adding the “index hint” statement to an Axapta select, it DOES mean that this index will be used by the database (and no other one).

Q. How many types of data validation methods are written on table level?
validateField(),validateWrite(),validateDelete(),aosvalidateDelete(),
aosvalidateInsert(), aosvalidateRead(),aosvalidateUpdate().

Q. How many types of relations are available in Axapta, Explain each of them.
Normal Relation: enforce referential integrity such as foreign keys. For displaying lookup on the child table.
Field fixed: works as a trigger to verify that a relation is active, if an enum field in the table has a specific value then the relation is active. It works on conditional relations and works on enum type of data.
Ex- Dimension table
Related field fixed: works as a filter on the related table.it only shows records that match the specified value for an enum field on the related table.

Q. Difference between Primary & Cluster index.
Primary index: It works on unique indexes. The data should be unique and not null. Retrieve data from the database.
Clustered Index: It works on unique and non unique indexes.retrieve data from the AOS.
The advantages of having a cluster index are as follows:
1. Search results are quicker when records are retrieved by the cluster index, especially if records are retrieved sequentially along the index.
2. Other indexes that use fields that are a part of the cluster index might use less data space.
3. Fewer files in the database; data is clustered in the same file as the clustering index. This reduces the space used on the disk and in the cache.
4. The disadvantages of having a cluster index are as follows:
5. It takes longer to update records (but only when the fields in the clustering index are changed).
6. More data space might be used for other indexes that use fields that are not part of the cluster index (if the clustering index is wider than approximately 20 characters).

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Apache Solr Interview Questions

If you're looking for Apache Solr Interview Questions, you are at right place. There are lot of opportunities from many reputed companies in the world. According to research Apache Solr has a market share of about 15.89%. So, You still have opportunity to move ahead in your career in Apache Solr. Mindmajix offers advanced Apache Solr Interview Questions that helps you in cracking your interview & acquire dream career.

Q. WHAT IS APACHE SOLR?
Apache Solr is a standalone full-text search platform to perform searches on multiple websites and index documents using XML and HTTP. Built on a Java Library called Lucence, Solr supports a rich schema specification for a wide range and offers flexibility in dealing with different document fields. It also consists of an extensive search plugin API for developing custom search behavior.

Q. WHAT FILE CONTAINS CONFIGURATION FOR DATA DIRECTORY?
Solrconfig.xml file contains configuration for data directory.

Q. WHAT FILE CONTAINS DEFINITION OF THE FIELD TYPES AND FIELDS OF DOCUMENTS?
schema.xml file contains definition of the field types and fields of documents.

Q. WHAT ARE THE FEATURES OF APACHE SOLR?

• Allows Scalable, high performance indexing Near real-time indexing
• Standards-based open interfaces like XML, JSON and HTTP
• Flexible and adaptable faceting
• Advanced and Accurate full-text search
• Linearly scalable, auto index replication, auto failover and recovery
• Allows concurrent searching and updating
• Comprehensive HTML administration interfaces
• Provides cross-platform solutions that are index-compatible

Q. WHAT IS APACHE LUCENE?
Supported by Apache Software Foundation, Apache Lucene is a free, open-source, high-performance text search engine library written in Java by Doug Cutting. Lucence facilitates full-featured searching, highlighting, indexing and spellchecking of documents in various formats like MS Office docs, HTML, PDF, text docs and others.

Q. WHAT IS REQUEST HANDLER?
When a user runs a search in Solr, the search query is processed by a request handler. SolrRequestHandler is a Solr Plugin, which illustrates the logic to be executed for any request.Solrconfig.xml file comprises several handlers (containing a number of instances of the same SolrRequestHandler class having different configurations).

Q. WHAT ARE THE ADVANTAGES AND DISADVANTAGES OF STANDARD QUERY PARSER?
Also known as Lucence Parser, the Solr standard query parser enables users to specify precise queries through a robust syntax. However, the parser’s syntax is vulnerable to many syntax errors unlike other error-free query parsers like DisMax parser.

Q. WHAT ALL INFORMATION IS SPECIFIED IN FIELD TYPE?
A field type includes four types of information:

• Name of field type
• Field attributes
• An implementation class name
• If the field type is Text Field , a description of the field analysis for the field type. 

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How to build your first advanced dashboard in tableau?

Building your First Advanced Dashboard

Creating dashboards with tableau is an interactive process, there isn’t a  “one best method”. Starting with a basic concept, discoveries made along the way lead to design refinements. Feedback from your target audience provides the foundation for additional enhancements. With traditional BI tools, this is a time-consuming process. Tableau’s drop and drag ease of using facilities resulted in the rapid evolution of designs and also started encouraging discovery.

Introducing the dashboard worksheet

After creating multiple, complementary worksheets, you can combine them into an integrated view if the data is using the dashboard worksheet. Figure 8.8 shows an empty dashboard workspace.
The top-left half of the dashboard shelf displays all of the worksheets contained in the workbook. The bottom half of the same space provides access to another object controls for adding text, images, blank space, or live web pages in the dashboard workspace. The worksheets and other design objects are placed into the “drop sheets here” area. The bottom left dashboard area contains controls for specifying the size of the dashboard and  a check box for adding a dashboard title.           

You are going to step through the creation of a dashboard using the access database file that ships with tableau called coffee chain. You will create the dashboard by employing the best practices, recommended earlier in the post.

The example dashboard is suitable for a weekly or monthly recurring reports. The specifications have been defined and are demanding. The example utilizes a variety of visualizations, dashboard objects and actions. It will include a main dashboard and a secondary dashboard that will be linked together via filter actions.

                                                      Figure 8.8: Tableau’s dashboard worksheet
Read through the rest of the post first to get an overview of the process. Then, step through each section and build the dashboard by yourself. When completed, your dashboard should look like figure 8.9

                                               Figure 8.9: Completed coffee chain dashboard example
The dashboard follows the 4-pane layout recommended earlier in the best practices section of this post, but it is actually a 5-panel design with the small select year cross-tab acting as a filter via a filter action. The main dashboard in figure 8.9 includes a variety of worksheet panes, an image object with a logo, text objects, dynamic title elements, and a text object containing an active web link. The example, employs a cascading design that links the main dashboard to a secondary dashboard via a filter action. The secondary dashboard contains more granular data in a crosstab and an embedded webpage that is filtered by hovering your mouse over the crosstab. This example is designed to use many of tableau’s advanced  dashboard features  included in tableau desktop version 8 and were included in MINDMAJIX TABLEAU TRAINING. The major steps required to complete this example are:

1. Download the post “bringing it all together with dashboards” dashboard exercise workbook from the book’s companion website. Refer to Appendix C: “inter works book website” for additional details.
2. Define the dashboard size and position the dashboard objects in the dashboard workspace.
3. Enhance title elements, refine axis headers, and place image and text objects into the primary dashboard.
4. Create a secondary dashboard with a detailed crosstab, webpage object and navigation pane.
5. Add filter, highlight and URL actions to the dashboards.
6. Finish the dashboard by enhancing the tooltips and testing all filtering and navigation. Add a read me dashboard to explain how the dashboard is intended to be used to data sources and for any calculations created that may not be obvious to the audience.

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What Is Artificial Neural Network And How It Works?

Introduction:

In order to understand the topic of the day, we need to firstly understand what a neural network means? The term Neural hails from the name of the nervous system basic unit called the ‘neuron’ and hence a network of such is called a Neural Network. That would be the network of neurons in a human brain, but what if the same power is imbibed into an artificial set of things which can simulate the same behavior – that’s the advent of Artificial Intelligence Neural Networks.

Artificial Neural Networks, ANN for short, have become pretty famous and is also considered the hot topic of interest and finds its application in chat-bots that are often used in the text classification. Being true to yourself, if and only if you are a neuroscientist, the analogy of using the brain isn’t going to illustrate much. Software analogies to synapses and neurons in animal brain have been on the rise while the neural networks in software industry has already been in the industry for decades.

What does artificial neural network mean?

Artificial Neural Networks can be best described as the biologically inspired simulations that are performed on the computer to do a certain specific set of tasks like clustering, classification, pattern recognition etc. In general, Artificial Neural Networks is a biologically inspired network of neurons (which are artificial in nature) configured to perform a specific set of tasks.

How does artificial neural networks work?

Artificial Neural Networks can be best viewed as weighted directed graphs, where the nodes are formed by the artificial neurons and the connection between the neuron outputs and neuron inputs can be represented by the directed edges with weights. The Artificial Neural Network receives the input signal from the external world in the form of a pattern and image in the form of a vector. These inputs are then mathematically designated by the notations x(n) for every n number of inputs.

Each of the input is then multiplied by its corresponding weights (these weights are the details used by the artificial neural networks to solve a certain problem). In general terms, these weights typically represent the strength of the interconnection amongst neurons inside the artificial neural network. All the weighted inputs are summed up inside the computing unit (yet another artificial neuron).

If the weighted sum equates to zero, a bias is added to make the output non-zero or else to scale up to the system’s response. Bias has the weight and the input to it is always equal to 1. Here the sum of weighted inputs can be in the range of 0 to positive infinity. To keep the response in the limits of a desired value, a certain threshold value is benchmarked. And then the sum of weighted inputs is passed through the activation function.

The activation function in general is the set of transfer functions used to get the desired output of it. There are various flavors of the activation function, but mainly either linear or non-linear sets of functions. Some of the most commonly used set of activation functions are the Binary, Sigmoidal (linear) and Tan hyperbolic sigmoidal (non-linear) activation functions. Now let us take a look at each of them, to certain detail:

Binary:

The output of the binary activation function is either a 0 or a 1. To attain this, there is a threshold value set up. If the net weighted input of the neuron is greater than 1 then the final output of the activation function is returned as 1 or else the output is returned as 0.

Sigmoidal Hyperbolic:

The Sigmoidal Hyperbola function in general terms is an ‘S’ shaped curve. Here tan hyperbolic function is used to approximate output from the actual net input. The function is thus defined as:

f (x) = (1/1+ exp(-????x))

where ?????is considered the?steepness parameter.

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Clustering entities - JBoss

Entities do not provide remote services like session beans, so they are not concerned with the load-balancing logic or session replication. You can, however, use a cache for your entities to avoid roundtrips to the database. JBossAS7EJB 3.0 persistence-layer JPA implementation is based on the Hibernate framework and, as such, this framework has a complex cache mechanism, which is implemented both at Session level and at SessionFactory level.

The latter mechanism is called second-level caching . The purpose of a JPA/Hibernate second-level cache is to store entities or collections locally retrieved from the database or to maintain results of recent queries.

Enabling the second-level cache for your Enterprise applications needs some properties to be set. If you are using JPA to access the second-level cache, all you have to add in the persistence.xml configuration file is:

The first element, shared-cache-mode, is the JPA 2.0 way to specify whether the entities and entity-related state of a persistence unit will be cached. The sharedcache- mode element has five possible values, as indicated in the following table:

Shared Cache mode	Description
ALL	Causes all entities and entity-related state and data to be cached.
NONE	Causes caching to be disabled for the persistence unit.
ENABLE_SELECTIVE	Allows caching if the @Cacheable annotation is specified on the entity class.
DISABLE_SELECTIVE	Enables the cache and causes all entities to be cached except those for which @Cacheable (false) is specified.

The property named hibernate.cache.use_minimal_puts performs some optimization on the second-level cache, by reducing the amount of writes in the caches at the cost of some additional reads.

In addition, if you plan to use the Hibernate Query cache in your applications, you need to activate it with a separate property:

For the sake of completeness, we will also include here the configuration needed for using Infinispan as a caching provider for native Hibernate applications. This is the list of properties you have to add to your hibernate.cfg.xml: 

name=”hibernate.cache.region.factory_class”value=”org.hibernate.cache.infinispan.

name=”hibernate.cache.infinispan.cachemanager”value=”java:jboss/infinispan/hibernate”/> name=”hibernate.transaction.manager_lookup_class”value=”org.hibernate.transaction. value=”true”/> 

As you can see, the configuration is a bit more verbose because you have to tell Hibernate to use Infinispan as a caching provider. This requires setting the correct Hibernate transaction factory, using the hibernate.transaction.factory_class property.

Next, the property hibernate.cache.infinispan.cachemanager exposes the CacheManager used by Infinispan. By default, Infinispan binds in the JNDI a shared CacheManager under the key java : jboss /infinispan/hibernate. This will be in charge to handle the second-level cache on the cached objects.

Finally, the property hibernate.cache.region.factory_class tells Hibernate to use the Infinispan second-level caching integration, using the previous Infinispan CacheManager found in JNDI as the source for Infinispan cache’s instances.

Caching entities

Unless you have set shared-cache-mode to ALL, Hibernate will not cache entity automatically. You have to select which entities or queries need to be cached. This is definitely the safest option since indiscriminate caching can actually hurt performance.

The following example shows how to do this for JPA entities using annotations.

import javax.persistence.*;
import org.hibernate.annotations.Cache;
import org.hibernate.annotations.CacheConcurrencyStrategy;
@Entity
@Cacheable
@Cache(usage = CacheConcurrencyStrategy.TRANSACTIONAL, region
=”properties”)
public class Property {
@Id
@Column(name=”key”)
private String key;
@Column(name=”value”)
private String value;
// Getter & setters omitted for brevity
}

The @javax.persistence.Cacheable dictates whether the Hibernate shared cache should be used for instances of the entity class and is applicable only when the sharedcache- mode is set to one of the selective modes.

The @org.hibernate.annotations.Cache annotation is the older annotation used to achieve the same purpose of @Cacheable. You can still use it for defining which strategy for controlling concurrent access to cache contents Hibernate should use.

The CacheConcurrencyStrategy.TRANSACTIONAL provides support for an Infinispan fully-transactional JTA environment.

If there are chances that your application data is read but never modified, you can apply the CacheConcurrencyStrategy.READ_ONLY that does not evict data from the cache (unless performed programmatically).

@Cache(usage=CacheConcurrencyStrategy.READ_ONLY)

Finally, the other attribute that can be defined is the caching region where entities are placed. If you do not specify a cache region for an entity class, all instances of this class will be cached in the _default region. Defining a caching region can be useful if you want to perform a fine-grained management of caching areas.

Caching queries

The query cache can be used to cache data from a query so that if the same query is issued again, it will not hit the database but return the cached value.

In the following example, the query result set named listUsers is configured to be cached using the @QueryHint annotation inside a @NamedQuery:
@NamedQueries(
{@
NamedQuery(
name = “listUsers”,
query = “FROM User c WHERE c.name = :name”,
hints = { @QueryHint(name = “org.hibernate.cacheable”, value =
“true”) }
)}
)
public class User {
@Id
@Column(name=”key”)
private String key;
@Column(name=”name”)
private String name;
. . . . .
}


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How code is reviewed in Gerrit

This record document fills in as your book's prelude, an incredible place to depict your book's substance and ideas.Code audit is a basic piece of our commitment work process. The rule is essential: any fix must be inspected by others before being combined.

This implies your code will require analysts. Check our guidance for getting surveys.

It's imperative to us to have an audit before-combine work process for center and furthermore for any augmentation we convey. We will likewise offer that choice to any augmentation creator who needs it for their expansion. The one exemption is localisation and internationalization confers, which will have the capacity to be pushed without survey.

Who can survey? Gerrit venture owners

In the wake of making a Gerrit account, anybody can remark on submits and flag their reactions and endorsements. Anybody can give a nonbinding "+1" to any submit. In any case, for any given vault ("Gerrit venture"), just a little gathering of individuals will be able to endorse code inside Gerrit and union it into the storehouse. This super approval is a "+2" despite the fact that that is a deceptive name, since two +1 endorsements DO NOT indicate a +2. These individuals are "Gerrit venture proprietors". Find out about turning into a Gerrit venture proprietor.

Indeed, even inside a Gerrit venture, we can likewise determine specific branches that lone particular individuals can maneuver into.

Step by step instructions to remark on, survey, and consolidation code in Gerrit

A naturally transferred test change set

Next to each other diff

Anybody can remark on code in Gerrit.

Sign in to Gerrit. On the off chance that you know the change set you need to take a gander at go to that. Something else, utilize the pursuit box and take a stab at seeking. You can look by creator ("Owner"), Gerrit venture, branch, change sets you've featured, and so forth. The Gerrit seek documentation covers the majority of the diverse pursuit administrators you can utilize.

The changeset has a couple of critical fields, connections and catches:

Commentators. 'jenkins-bot' is the auto reviewer that auto-checks anything that finishes the Jenkins tests. It will report a red or green stamp contingent upon whether the manufacture passes.

Analysts: Add… . Physically pings somebody to ask for their audit. It'll appear in their Gerrit dashboard.

Records: Open All. Opens the diff (each record in a different program tab). You can double tap on a line and after that press C to remark on that line, at that point spare a draft remark! At that point, tap the green "Up to change" bolt to backpedal to the changeset, and snap "Answer… " to distribute your remark.

Answer… ("Add remark"). Distribute your musings on the confer, including a general remark or potentially inline remarks you included (see above).

On the off chance that, upon code audit, you support, utilize "+1" under "Answer… "; something else, utilize "- 1" to object. These numbers are nonbinding, won't cause consolidations or dismissals, and have no formal impact on the code audit.

Surrender (you'll see this on the off chance that you composed this diff). This activity expels the diff from the consolidation line, yet abandons it in Gerrit for authentic purposes.

Contrasting patch sets[edit]

Each time you change your confer and submit it for survey, another fix set is made. You can look at the changed fix sets this way:

Under Files, select either Open All or pick a particular record leaned to open that document.

On the left side under Patch Set, Base is preselected. On the privilege of the screen under Patch Set, the most recent fix set is preselected. Alter the chose fix sets to your requirements.

Formally evaluating and blending or dismissing code[edit]

On the off chance that you are one of the Gerrit venture proprietors, you'll additionally observe:

Forsake catch

under Reply, extra Code-Review choices to +2 (support) or - 2 (veto) a diff, and a Post catch (distribute your remark and consolidation diff into the branch, in 1 stage)

Submit catch (consolidate - just valuable on the off chance that you or another person has officially given a +2 endorsement to the diff, however not blended it)

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