What is the purpose of NODE_PROPERTIES table in the database and how do we get this table populated with key value pairs and how do we query? And how do we query data in other NODE tables like NODE_INFOS, NODE_NAMED_IDENTITIES , NODE_INFO_HOSTS? Is there any service level function available in CordaRPCClient to do that? We would like to store some extra properties for each node
The NODE_PROPERTIES table is used for internal purposes to store information that doesn't justify having its own table (currently, whether or not the node was in flow-drain mode when it was last stopped).
Feel free to store additional key-value pairs there, as long as they don't clash with keys used for internal purposes (a clash is unlikely, as we currently use long key-names to store information in this table).
You can get access to the node's database via the node's ServiceHub, which is available inside flows and services. The Flow DB sample shows an example of a service that connects, reads and writes directly to the node's database: https://github.com/corda/samples.
You can also connect directly to the node via JDBC (e.g. from a client or server). The node lists its JDBC database connection string at start-up. You can also set it in the node's configuration file, as shown here: https://docs.corda.net/corda-configuration-file.html#examples.
Related
I have an Ionic App using SQLite. I don't have any problems with implementation.
The issue is that I need to import an SQL file using SQLitePorter to populate the database with configuration info.
But also, on the same database I have user info, so my question is:
Everytime I start the app, it will import the sql file, fill the database and probably overwrite my user data too? Since it is all on the same base?
I assume that you can always init your table using string queries inside your code. The problem is not that you are importing a .sql file. Right?
According to https://www.sqlitetutorial.net/sqlite-create-table/ it is obvious that you always create a table with [IF NOT EXISTS] switch. Writing a query like :
CREATE TABLE [IF NOT EXISTS] [schema_name].table_name (
column_1 data_type PRIMARY KEY);
you let sqlite to decide if it's going to create a table with the risk to overwrite an existing table. It is supposed that you can trust that sqlite is smart enough, not to overwrite any information especially if you use 'BEGIN TRANSACTION' - 'COMMIT' procedure.
I give my answer assuming that you have imported data and user data in distinct tables, so you can manipulate what you populate and what you don't. Is that right?
What I usually do, is to have a sql file like this:
DROP TABLE configutation_a;
DROP TABLE configutation_b;
CREATE TABLE configutation_a;
INSERT INTO configutation_a (...);
CREATE TABLE configutation_b;
INSERT INTO configutation_b (...);
CREATE TABLE IF NOT EXIST user_data (...);
This means that every time the app starts, I am updating with the configuration data I have at that time (that's is why we use http.get to get any configuration file from a remote repo in the future) and create user data only if user_data table is not there (hopefully initial start).
Conclusion: It's always a good practice, in my opinion, to trust a database product 100% and abstractly let it do any transaction that might give you some risk if you implemented your self in your code; since it gives a tool for that.For example, the keyword [if not exists], is always safer than implementing a table checker your self.
I hope that helps.
PS: In case you refer in create database procedure, SQLite, connects to a database file and it doesn't exist, it creates it. For someone comfortable in sqlite command line, when you type
sqlite3 /home/user/db/configuration.db will connect you with this db and if the file is not there, it will create it.
Is it possible to provide a default value or a query to provide a value to an unmapped column in the target table using Redgate SQL Data Compare?
To explain the scenario I have a configuration database that holds settings data for several database instances. The data is all in the same shape, but the config database has an additional InstanceID field in most tables. This allows me to filter my compare to only compare against the InstanceID relating to the source Instance database. However if I generate Insert scripts they fail because the Target Instance ID fields are non nullable. I want to provide a default value that is then used in the Insert Scripts. Is this doable?
SQL Data Compare doesn't have an easy way of doing this I'm afraid.
There is one way to do it - you could create a view that selects everything from the source table along with a computed column, which just provides the "default value" that you want to insert. Then you can map the view to the table in the target database and compare them, deploying from the result.
I hope this helps.
What is the Amazon-recommended way of changing the schema of a large table in a production DynamoDB?
Imagine a hypothetical case where we have a table Person, with primary hash key SSN. This table may contain 10 million items.
Now the news comes that due to the critical volume of identity thefts, the government of this hypothetical country has introduced another personal identification: Unique Personal Identifier, or UPI.
We have to add an UPI column and change the schema of the Person table, so that now the primary hash key is UPI. We want to support for some time both the current system, which uses SSN and the new system, which uses UPI, thus we need both these two columns to co-exist in the Person table.
What is the Amazon-recommended way to do this schema change?
There are a couple of approaches, but first you must understand that you cannot change the schema of an existing table. To get a different schema, you have to create a new table. You may be able to reuse your existing table, but the result would be the same as if you created a different table.
Lazy migration to the same table, without Streams. Every time you modify an entry in the Person table, create a new item in the Person table using UPI and not SSN as the value for the hash key, and delete the old item keyed at SSN. This assumes that UPI draws from a different range of values than SSN. If SSN looks like XXX-XX-XXXX, then as long as UPI has a different number of digits than SSN, then you will never have an overlap.
Lazy migration to the same table, using Streams. When streams becomes generally available, you will be able to turn on a Stream for your Person table. Create a stream with the NEW_AND_OLD_IMAGES stream view type, and whenever you detect a change to an item that adds a UPI to an existing person in the Person table, create a Lambda function that removes the person keyed at SSN and add a person with the same attributes keyed at UPI. This approach has race conditions that can be mitigated by adding an atomic counter-version attribute to the item and conditioning the DeleteItem call on the version attribute.
Preemptive (scripted) migration to a different table, using Streams. Run a script that scans your table and adds a unique UPI to each Person-item in the Person table. Create a stream on Person table with the NEW_AND_OLD_IMAGES stream view type and subscribe a lambda function to that stream that writes all the new Persons in a new Person_UPI table when the lambda function detects that a Person with a UPI was changed or when a Person had a UPI added. Mutations on the base table usually take hundreds of milliseconds to appear in a stream as stream records, so you can do a hot failover to the new Person_UPI table in your application. Reject requests for a few seconds, point your application to the Person_UPI table during that time, and re-enable requests.
DynamoDB streams enable us to migrate tables without any downtime. I've done this to great effective, and the steps I've followed are:
Create a new table (let us call this NewTable), with the desired key structure, LSIs, GSIs.
Enable DynamoDB Streams on the original table
Associate a Lambda to the Stream, which pushes the record into NewTable. (This Lambda should trim off the migration flag in Step 5)
[Optional] Create a GSI on the original table to speed up scanning items. Ensure this GSI only has attributes: Primary Key, and Migrated (See Step 5).
Scan the GSI created in the previous step (or entire table) and use the following Filter:
FilterExpression = "attribute_not_exists(Migrated)"
Update each item in the table with a migrate flag (ie: “Migrated”: { “S”: “0” }, which sends it to the DynamoDB Streams (using UpdateItem API, to ensure no data loss occurs).
NOTE: You may want to increase write capacity units on the table during the updates.
The Lambda will pick up all items, trim off the Migrated flag and push it into NewTable.
Once all items have been migrated, repoint the code to the new table
Remove original table, and Lambda function once happy all is good.
Following these steps should ensure you have no data loss and no downtime.
I've documented this on my blog, with code to assist:
https://www.abhayachauhan.com/2018/01/dynamodb-changing-table-schema/
I'm using a variant of Alexander's third approach. Again, you create a new table that will be updated as the old table is updated. The difference is that you use code in the existing service to write to both tables while you're transitioning instead of using a lambda function. You may have custom persistence code that you don't want to reproduce in a temporary lambda function and it's likely that you'll have to write the service code for this new table anyway. Depending on your architecture, you may even be able to switch to the new table without downtime.
However, the nice part about using a lambda function is that any load introduced by additional writes to the new table would be on the lambda, not the service.
If the changes involve changing the partition key, you can add a new GSI (global secondary index). Moreover, you can always add new columns/attributes to DynamoDB without needing to migrate tables.
I am using a global application user account to access database A. This user account does not have permissions to modify database A's schema (ie, create tables, modify tables, etc). This user also has access to database B, but only views. I need to run SQL to feed data from a view in database B into a table in database A.
In a perfect world, I would be able to use this SQL:
create database_a.mytable as (select * from database_b) with no data
However, the user can't create tables in database A. If I could get the DDL of the select statement then I could log in under my personal account (which doesn't have any access to database B) and run the DDL in database A to create the table.
The only other option is to manually write the SQL, but I don't want to do that, especially since this view I am wanting to copy has many columns of varying data types and sizes.
Edit: I may be getting closer. I just experimented with this:
show (select * from database_b.myview)
However, it generated the DLL of every single table that is used in the view itself, as well as the definition for the view. This doesn't really help me since I just want the schema of the select statement itself. In other words, I need what would be generated if I were to use the create table as statement mentioned above.
Edit for Rob: Perhaps "DDL" was the wrong term to use. Using show view db.myview just shows the definition of the view, not the schema it represents. In my above example of create table as, I show how you can create a table that mimics the schema of a result set returned in a select. It generates a DDL on the back end for creating a table and then executes that DDL to actually create the table. You can then say show table db.newtable and see the new table's DDL. I want to get that DDL directly from a select statement so that I can copy it, log out of the app account, into my personal account, and then execute the DDL to create the table.
This is only to save me the headache of having to type out the DDL manually by hand to save time and reduce typing errors, especially since the source view has so many columns. That said, I think hitting up the DBA or writing some snazzy stored procedure to do dynamic stuff would be a bit over the top for my needs. I think there has to be a way to get the DDL for creating a table schema directly from a select statement.
Generate DDL Statements for objects:
SHOW TABLE {DatabaseB}.{Table1};
SHOW VIEW {DatabaseB}.{View1};
Breakdown of columns in a view:
HELP VIEW {DatabaseB}.{View1};
However, without the ability to create the object in the target database DatabaseA your don't have much leverage. Obviously, if the object already existed INSERT INTO SELECT ... FROM DatabaseB.Table1 or MERGE INTO would be options that you already explored.
Alternative Solution
Would it be possible to have a stored procedure created that dynamically created the table based on the view name that is provided? The global application account would simply need privilege to execute the procedure. Generally the user creating the stored procedure would need the permissions to perform the actions contained within the stored procedure. (You have some additional flexibility with this in Teradata 13.10.)
There are some caveats with this approach. You are attempting to materialize views that could reference anywhere from hundreds to billions of records. These aren't simple 1:1 views that are put on top of the target tables. Trying to determine the required space in the target database to materialize the view will be difficult. Performance can and will vary depending on the complexity of the view and the data volumes. This will not be a fast-path or data block optimized operation.
As a DBA, I would be concerned with this approach being taken on by a global application account without fully understanding the intent. I trust you have an open line of communication with the DBA(s) involved for supporting this system. I'm sure there are reasons for your madness that can't be disclosed here.
Possible Solution - VOLATILE TABLE
Unless the implicit privilege for CREATE TABLE has been revoked from the global application account this solution should work.
Volatile tables do not require perm space. There table definitions persist for the duration of the session and any data inserted into them relies on the spool space of the user who instantiated it.
CREATE VOLATILE TABLE {Global Application UserID}.{TableA_Copy} AS
(
SELECT *
FROM {DatabaseB}.{TableA}
)
WITH NO DATA
NO PRIMARY INDEX
ON COMMIT PRESERVE ROWS;
SHOW TABLE {Global Application UserID}.{TableA_Copy};
I opted to use a Teradata 13.10 feature called NO PRIMARY INDEX. By default, CREATE TABLE AS will take the first column of the SELECT statement and make it the PRIMARY INDEX of the table. This could lead to skewing and perm space issues in your testing depending on the data demographics. You can specify an explicit PRIMARY INDEX on your own as you understand the underlying data. (See the DDL manuals for details on the syntax if you're uncertain.)
The use of ON COMMIT PRESERVE ROWS for the intent of this example is probably extraneous. But in reality if you popped any data into that table for testing this clause would be beneficial in Teradata mode as the data would otherwise be lost immediately after the CREATE TABLE or any other data manipulation was performed against the volatile table.
I currently have multiple queries that query data from a few tables linked through ODBC, and some temporary tables that are edited through the user interface. I have complex criteria in my queries such as:
SELECT * from ThingsData
WHERE (Thing In(SELECT Thing from ListOfThings) AND getThingFlag() = True);
In this case Thing is a field and ListOfThings is a temporary table that the user defines from the user interface. Basically, the user puts together a list of the field Thing that he/she wants to filter the data based on and I want to query only the data that matches the Thing values that the user adds to his/her list. Currently, the data I am querying is in the linked ODBC table, and the temp table ListOfThings is just a regular, local table and everything works peachy. I want to get rid of the linked table and use a pass through query instead. However, when i do that, unless the criteria is incredibly simplistic, i get an error:
"ODBC--Call Failed. Invalid object name ListOfThings."
If I dont have any criteria it works fine.
Long story short: In a pass through query, how do I apply criterias that include SELECTs and functions from my modules and just basically filter the pass through table based on data from my local tables?
What is at the other end of that ODBC link? In a pass-through query you will have to honor the syntax required by the database server, not Access syntax. I would first suspect that you can't have mixed case table names and I would try listofthings as the name.
If you have a tool that can be used to test queries directly against the database server, get the query working there and then simply cut and paste it into an Access pass-through query.