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A result set filter is invoked (potentially) for every row in a result set. The filter can modify the row, add more rows, drop the row, or return an error. This filter works for all result sets, whether they result from a CQL statement or from the execution of a stored procedure.
Unlike other filter, the result set filter has two important objects predefined:
context.row is the current ResultRow. The values of its columns can be changed, and it can easily be hidden.
context.packet is the ResultRows packet that contains the row. It may be useful if you need visibility to other rows, but keep in mind that a large result set will be broken into multiple ResultRows packets.
Parameters
Parameters
All parameters are optional. If no parameter is specified, then the filter will be invoked for every row of every result set.
User pattern
User pattern
If specified, a comma-separated (or line break separated) list of database user names or regular expressions for database user names.
Client IPs
Client IPs
A comma-separated (or line-break separated) list of IP4 or IP6 addresses or regular expressions for IP addresses. If specified, this filter will only be invoked when the client's IP address matches.
Keyspace pattern
Keyspace pattern
If specified, the filter will not be invoked unless it contains at least one column from a table in the specified keyspace. Can be a string or a regular expression.
Table pattern
Table pattern
If specified, the filter will not be invoked unless it contains at least one column from the specified table. Can be a string or a regular expression.
Query pattern
Query pattern
A series of strings and/or regular expressions, separated by commas or newlines. If this is specified, the filter will be invoked only if the CQL query that caused this result set matches the pattern.
Column patterns
Column patterns
A series of name=value pairs, separated by commas or newlines. The value is a regular expression, which means special characters like period must be escaped.
And/or
And/or
If more than one column pattern is specified, this determines whether they must all be true (and) or any one of them (or).
Action
Action
Can be either code or hide. If it's code, then the code is executed. If it's hide, then the row is dropped from the result set, and the code is not executed.
Example: hide some products
Example: hide some products
The following examples use the Cassandra tutorial database.
The requirement is that toys over $20 should be invisible to users in France or Germany (i.e. users whose user name starts with "fr_" or "de_")
The filter will be invoked whenever a query of the form:
select * from gallium_demo.products
is executed. We can create a result set filter with the proper parameters, and add a bit of code to hide the data.
The parameters for the filter are:
User pattern: regex:fr_.*,de_.*
Keyspace pattern: gallium_demo
Table pattern: products
Column patterns: category=Toys
This will ensure that this filter will be invoked for all toys.
Next we add a bit of code that checks the price and hides the row if necessary:
if (context.row.price > 20) {
context.row.remove();
}
If we now re-run the query:
select * from gallium_demo.customers
we only see 5 rows. The database is of course untouched -- all we changed was the result set on its way to the client.
We can further qualify this, for instance by making this filter run only for certain users, or make it depend on the query.
Example: mask some values
Example: mask some values
Let's say there is a query that returns data that should not be seen by some users. The rule is:
For users in France and Germany (i.e. users whose user name starts with "fr_" or "de_"), customers' phone numbers should be hidden.
We can create a result set with the proper parameters, and add a bit of code to hide the data.
The parameters for the filter are:
User pattern: regex:fr_.*,de_.*
Keyspace pattern: gallium_demo
Table pattern: customer
The code for the filter will be invoked when these conditions are satisfied, and can hide the customer's phone numbers with:
if (context.row.phones) {
context.row.phones = null;
}
We could also mask, say, the home phone number (which is stored in a compound map) with:
if (context.row.phones && context.row.phones.home) {
context.row.phones.home.phone_number = "XXXXXXX";
}
Example: add a synthetic row to the result set
Example: add a synthetic row to the result set
We can add new rows to the result set by cloning the current row and modifying it.
We create a filter with the parameters:
Keyspace pattern: gallium_demo
Table pattern: products
Column patterns: id=7
This will ensure that the code for the filter will only be executed for product #7, which we'll duplicate with the following code:
for (var i = 1; i <= 3; i++) {
let newRow = context.row.clone();
newRow.id = 1000000 + i;
newRow.name = 'Made-up product #' + i;
context.packets.addPacket(newRow);
}
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