org.apache.cassandra.transport.ProtocolException: Invalid or unsupported protocol version: 4

When I wanted to upgrade my Cassandra from 2.1.3 to 3.4 in Windows 7 64 bit, I have faced following error when starting cqlsh console.

E:\apache-cassandra-3.4\bin>cqlsh
Connection error: ('Unable to connect to any servers', {'127.0.0.1': ConnectionException(u'Did not get expected SupportedMessage response; instead, got: <ErrorMessage code=0000 [Server error] message="io.netty.handler.codec.DecoderException: org.apache.cassandra.transport.ProtocolException: Invalid or unsupported protocol version: 4">',)})

This was happening even when I downgrade my cqlversion as follows.

E:\apache-cassandra-3.4\bin>cqlsh --cqlversion=3.4.0
Connection error: ('Unable to connect to any servers', {'127.0.0.1': ConnectionException(u'Did not get expected SupportedMessage response; instead, got: <ErrorMessage code=0000 [Server error] message="io.netty.handler.codec.DecoderException: org.apache.cassandra.transport.ProtocolException: Invalid or unsupported protocol version: 4">',)})

E:\apache-cassandra-3.4\bin>python -V
Python 2.7.6
E:\apache-cassandra-3.4\bin>cqlsh --version
cqlsh 5.0.1

This is due to protocol version (4) unsupported by cql.
Edit <cassandra_home>\bin\cqlsh.py to make following inclusions so that it accepts --protocolversion argument along with cqlsh command. It's advisable to take backup of cqlsh.py file before editing it.

I have given edited lines below. Add only the lines that are marked with + (plus sign). Other lines are given for reference of places to make change. 

.
.
parser.add_option('--cqlversion', default=DEFAULT_CQLVER,
                  help='Specify a particular CQL version (default: %default).'
                       ' Examples: "3.0.3", "3.1.0"')
+ parser.add_option("--protocolversion", default=DEFAULT_PROTOCOL_VERSION, help='Specify protocol version (default: %default).')
parser.add_option("-e", "--execute", help='Execute the statement and quit.')

.
.
    try:
        port = int(port)
    except ValueError:
        parser.error('%r is not a valid port number.' % port)

+    if options.protocolversion:

+       try:
+            options.protocolversion = int(options.protocolversion)
+        except ValueError:
+            options.protocolversion=DEFAULT_PROTOCOL_VERSION

    return options, hostname, port

.
.
                      connect_timeout=options.connect_timeout,
                      encoding=options.encoding,
 +                    protocol_version=options.protocolversion)
    except KeyboardInterrupt:
        sys.exit('Connection aborted.')

Once the changes are done, save it and restart Cassandra server. Now execute cqlsh with following command.

E:\apache-cassandra-3.4\bin>cqlsh --protocolversion=3

Still you may face any issue like following.

Connection error: ('Unable to connect to any servers', {'127.0.0.1': ProtocolError("cql_version '3.4.0' is not supported by remote (w/ native protocol). Support
ed versions: [u'3.2.0']",)})

In such case, execute cqlsh command as follows and the issue would be resolved now.

E:\apache-cassandra-3.4\bin>cqlsh --protocolversion=3 --cqlversion=3.2.0

Connected to Test Cluster at 127.0.0.1:9042.
[cqlsh 5.0.1 | Cassandra 2.1.3 | CQL spec 3.2.0 | Native protocol v3]
Use HELP for help.
WARNING: pyreadline dependency missing.  Install to enable tab completion.
cqlsh>

What are VIEWS in Oracle/PLSQL?

Oracle/PLSQL: VIEWS

Let's learn to create, update, and drop Oracle VIEWS with syntax and examples.

What is a VIEW in Oracle?

An Oracle VIEW, in essence, is a virtual table that does not physically exist. Rather, it is created by a query joining one or more tables.

Create VIEW

Syntax

The syntax for the Oracle CREATE VIEW Statement is:

CREATE VIEW view_name AS 
SELECT columns FROM tables WHERE conditions;

view_name is the name of the Oracle VIEW that you wish to create.

Example

Here is an example of how to use the Oracle CREATE VIEW:

CREATE VIEW sup_orders AS 
SELECT suppliers.supplier_id, orders.quantity, orders.price 
FROM suppliers INNER JOIN orders 
ON suppliers.supplier_id = orders.supplier_id WHERE suppliers.supplier_name = 'Microsoft';

This Oracle CREATE VIEW example would create a virtual table based on the result set of the SELECT statement. You can now query the Oracle VIEW as follows:

SELECT * FROM sup_orders;

Update VIEW

You can modify the definition of an Oracle VIEW without dropping it by using the Oracle CREATE OR REPLACE VIEW Statement.

Syntax

The syntax for the Oracle CREATE OR REPLACE VIEW Statement is:

CREATE OR REPLACE VIEW view_name AS 
SELECT columns FROM table WHERE conditions;

Example

Here is an example of how you would use the Oracle CREATE OR REPLACE VIEW Statement:

CREATE or REPLACE VIEW sup_orders AS 
SELECT suppliers.supplier_id, 
orders.quantity, orders.price 
FROM suppliers INNER JOIN orders 
ON suppliers.supplier_id = orders.supplier_id 
WHERE suppliers.supplier_name = 'Apple';

This Oracle CREATE OR REPLACE VIEW example would update the definition of the Oracle VIEW called sup_orders without dropping it. If the Oracle VIEW did not yet exist, the VIEW would merely be created for the first time.

Drop VIEW

Once an Oracle VIEW has been created, you can drop it with the Oracle DROP VIEW Statement.

Syntax

The syntax for the Oracle DROP VIEW Statement is:

DROP VIEW view_name;

view_name is the name of the view that you wish to drop.

Example

Here is an example of how to use the Oracle DROP VIEW Statement:

DROP VIEW sup_orders;

This Oracle DROP VIEW example would drop/delete the Oracle VIEW called sup_orders.

Frequently Asked Questions

Question: Can you update the data in an Oracle VIEW?

Answer: A VIEW in Oracle is created by joining one or more tables. When you update record(s) in a VIEW, it updates the records in the underlying tables that make up the View.

So, yes, you can update the data in an Oracle VIEW providing you have the proper privileges to the underlying Oracle tables.

Question: Does the Oracle View exist if the table is dropped from the database?

Answer: Yes, in Oracle, the VIEW continues to exist even after one of the tables (that the Oracle VIEW is based on) is dropped from the database. However, if you try to query the Oracle VIEW after the table has been dropped, you will receive a message indicating that the Oracle VIEW has errors.

If you recreate the table (the table that you had dropped), the Oracle VIEW will again be fine.

What is an index in database? How does it work? What is its use?

Let’s begin with explaining why do we need a database index by going through a very simple example. Suppose that we have a database table called Student with three columns – Student_Name, Student_Age, and Scorecard. Assume that our Student table has thousands of rows. 

Now, let’s say that we want to run a query to find all the details of any students who are named ‘John’? So, we decide to run a simple query like this: 

SELECT * FROM Student 
WHERE Student_Name = 'John' 

What would happen without an index on the table?

Once we run that query, what exactly goes on behind the scenes to find students who are named John? Well, the database software would literally have to look at every single row in the Student table to see if the Student_Name for that row is ‘John’. And, because we want every row with the name ‘John’ inside it, we can not just stop looking once we find just one row with the name ‘John’, because there could be other rows with the name ‘John’. So, every row up until the last row must be searched – which means thousands of rows in this scenario will have to be examined by the database to find the rows with the name‘John’. This is what is called a full table scan.

How a database index can help improving performance

You might be thinking that doing a full table scan sounds inefficient for something so simple – shouldn’t software be smarter? It’s almost like looking through the entire table with the human eye – very slow and not at all sleek. But, as you probably guessed by the title of this article, this is where indexes can help a great deal.  

The whole point of having an index is to speed up search queries by essentially cutting down the number of records/rows in a table that need to be examined.

What is an index?

So, what is an index? Well, an index is a data structure (most commonly a B-tree) that stores the values for a specific column in a table. An index is created on a column of a table. So, the key points to remember are that an index consists of column values from one table, and that those values are stored in a data structure. The index is a data structure – remember that.

What kind of data structure is an index?

B-trees are the most commonly used data structures for indexes. The reason B-trees are the most popular data structure for indexes is due to the fact that they are time efficient – because look-ups, deletions, and insertions can all be done in logarithmic time. And, another major reason B- trees are more commonly used is because the data that is stored inside the B-tree can be sorted. The RDBMS typically determines which data structure is actually used for an index. But, in some scenarios with certain RDBMS’s, you can actually specify which data structure you want your database to use when you create the index itself.

 

How does a hash table index work?

Hash tables are another data structure that you may see being used as indexes – these indexes are commonly referred to as hash indexes. The reason hash indexes are used is because hash tables are extremely efficient when it comes to just looking up values. So, queries that compare for equality to a string can retrieve values very fast if they use a hash index. For instance, the query we discussed earlier (SELECT * FROM Student WHERE Student_Name = ‘John’) could benefit from a hash index created on the Student_Name column. The way a hash index would work is that the column value will be the key into the hash table and the actual value mapped to that key would just be a pointer to the row data in the table. Since a hash table is basically an associative array, a typical entry would look something like “John => 0×29856″, where 0×29856 is a reference to the table row where John is stored in memory. Looking up a value like “John” in a hash table index and getting back a reference to the row in memory is obviously a lot faster than scanning the table to find all the rows with a value of “John” in the Student_Name column.

 

The disadvantages of a hash index

Hash tables are not sorted data structures, and there are many types of queries which hash indexes can not even help with. For instance, suppose you want to find out all of the students who are less than 12 years old. How could you do that with a hash table index? Well, it’s not possible because a hash table is only good for looking up key value pairs – which means queries that check for equality (like “WHERE Student_name = ‘John’”). What is implied in the key value mapping in a hash table is the concept that the keys of a hash table are not sorted or stored in any particular order. This is why hash indexes are usually not the default type of data structure used by database indexes – because they aren’t as flexible as B-trees when used as the index data structure. 

 

What are some other types of indexes?

Indexes that use a R-tree data structure are commonly used to help with spatial problems. For instance, a query like “Find all of the Starbucks within 2 kilometers of me” would be the type of query that could show enhanced performance if the database table uses a R-tree index.
Another type of index is a bitmap index, which work well on columns that contain Boolean values (like true and false), but many instances of those values – basically columns with low selectivity.

 

How does an index improve performance?

Because an index is basically a data structure that is used to store column values, looking up those values becomes much faster. And, if an index is using the most commonly used data structure type – a B-tree – then the data structure is also sorted. Having the column values be sorted can be a major performance enhancement – read on to find out why.
Let’s say that we create a B-tree index on the Student_Name column. This means that when we search for students named “John” using the SQL we showed earlier, then the entire Student table does not have to be searched to find students named “John”. Instead, the database will use the index to find students named John, because the index will presumably be sorted alphabetically by the Student’s name. And, because it is sorted, it means searching for a name is a lot faster because all names starting with a “J” will be right next to each other in the index! It’s also important to note that the index also stores pointers to the table row so that other column values can be retrieved – read on for more details on that.

 

What exactly is inside a database index?

So, now you know that a database index is created on a column in a table, and that the index stores the values in that specific column. But, it is important to understand that a database index does not store the values in the other columns of the same table. For example, if we create an index on the Student_Name column, this means that the Student_Age and Scorecard column values are not also stored in the index. If we did just store all the other columns in the index, then it would be just like creating another copy of the entire table – which would take up way too much space and would be very inefficient.

 

An index also stores a pointer to the table row

So, the question is if the value that we are looking for is found in an index (like ‘John’) , how does it find the other values that are in the same row (like the scorecard of John and his age)? Well, it’s quite simple – database indexes also store pointers to the corresponding rows in the table. A pointer is just a reference to a place in memory where the row data is stored on disk. So, in addition to the column value that is stored in the index, a pointer to the row in the table where that value lives is also stored in the index. This means that one of the values (or nodes) in the index for an Student_Name could be something like (“John”, 0×89856), where 0×89856 is the address on disk (the pointer) where the row data for “John” is stored. Without that pointer all you would have is a single value, which would be meaningless because you would not be able to retrieve the other values in the same row – like the scorecard and the age of a student.

 

How does a database know when to use an index?

When a query like “SELECT * FROM Student WHERE Student_Name = ‘John’ ” is run, the database will check to see if there is an index on the column(s) being queried. Assuming the Student_Name column does have an index created on it, the database will have to decide whether it actually makes sense to use the index to find the values being searched – because there are some scenarios where it is actually less efficient to use the database index, and more efficient just to scan the entire table. 

 

Can you force the database to use an index on a query?

Generally, you will not tell the database when to actually use an index – that decision will be made by the database itself. Although it is worth noting that in most databases (like Oracle and MySQL), you can actually specify that you want the index to be used.

 

How to create an index in SQL:

Here’s what the actual SQL would look like to create an index on the Student_Name column from our example earlier: 

CREATE INDEX name_index
ON Student (Student_Name)

 

How to create a multi-column index in SQL:

We could also create an index on two of the columns in the Student table , as shown in this SQL: 

CREATE INDEX name_index
ON Student (Student_Name, Student_Age)

 

What is a good analogy for a database index?

A very good analogy is to think of a database index as an index in a book. If you have a book about dogs and you are looking for the section on Golden Retrievers, then why would you flip through the entire book – which is the equivalent of a full table scan in database terminology – when you can just go to the index at the back of the book, which will tell you the exact pages where you can find information on Golden Retrievers. Similarly, as a book index contains a page number, a database index contains a pointer to the row containing the value that you are searching for in your SQL.

 

What is the cost of having a database index?

So, what are some of the disadvantages of having a database index? Well, for one thing it takes up space – and the larger your table, the larger your index. Another performance hit with indexes is the fact that whenever you add, delete, or update rows in the corresponding table, the same operations will have to be done to your index. Remember that an index needs to contain the same up to the minute data as whatever is in the table column(s) that the index covers.
As a general rule, an index should only be created on a table if the data in the indexed column will be queried frequently.