I'm working on a tool that allows Python developers to write pythonic code to interact with a sqlite3 database, similar to sqlalchemy but without the "translation" phase. If I can generate a sqlite3 prepared statement, how can I directly pass it to the evaluation system?
As a rough example, here's how I roughly view a user being able to interact with my tool:
myTable = Table("field1", "field2", "field3")
mytable.insert("foo", "bar", "baz")
select = mytable.select("field1")
---------------
print(select)
>>> ["foo"]
There is no (public) API in SQLite3 that allows you to execute pre-built SQLite bytecode. The bytecode for an SQL statement can be viewed with the EXPLAIN SQL command, but this is meant for debugging and learning purposes, not for what you're trying to do.
And for most purposes, you shouldn't need this. If you feel that the time spent compiling a prepared statement will be a burden, sqlite3_stmt objects can be stored for the lifetime of the sqlite3 database connection it was created with. Prepared statements that have been executed can be reset, allowing them to be executed again. So as long as the database connection exists, you can compile the statement once and use it as many times as you need to.
But that's about it. There is no mechanism to persist a prepared statement beyond the lifespan of the sqlite3 connection. You can't extract the bytecode by any public API, and you can't use some bytecode you've obtained to reconstitute a prepared statement.
If you want persistence beyond the connection, then you need to store the SQL statement text in whatever place you want to be persistent, and then simply recompile the prepared statement when you reconnect to the database. That one recompilation (or many depending on how many you store) shouldn't be a particular burden, depending on the life span of your application.
Related
Daily, I query a few tables in SQL Developer, filtering to prior day activity, adding column to date stamp the data, then export to xlsx. Then I manually import each file to a MS SQL Server via SQL Server Import and Export Wizard. Takes many clicks, much waiting...
I'm essentially creating an archive in SQL Server, the application I'm querying overwrites data daily. I'm not a DBA of either database, I use the archived data to do validations and research.
It's tough to get my org to provide additional software, I've been trying to make this work via SQL Developer, SSMS Express ed, and other standard tools.
I'm looking to make this reasonably automated, either via scripts, scheduled tasks, etc. Appreciate suggestions that would work on my current situation, but if that isn't reasonable, and there's a very reasonable alternative, I can go back to the org to request software/access/assistance.
You can use SSIS to import the data directly from Oracle to SQL Server, unless you need the .xlsx files for another purpose. You can also export from Oracle to these, then load to SQL Server from these files if you do need the files. For the date stamp column, a Derived Column can be added within a Data Flow Task using the SSIS GETDATE() function for a timestamp in order to achieve the same result. This function returns a timestamp, and if only the date is necessary the (DT_DBDATE) function can cast it to a date data type that's compatible with this data type of SQL Server. Once you have the SSIS package configured, you can schedule in to run at regular intervals as a SQL Agent job. I'd also recommend installing the SSIS catalog (SSISDB) and using this the source to run the packages from. The following links shed more light on these areas.
SSIS
Connecting to Oracle from SSIS
Data Flow Task
Derived Column Transformation
Creating SQL Server Agent Jobs for SSIS packages
SSIS Catalog
Another option that you may consider (if it is supported in SQL Express) is using the BCP utility, which can be run from command line.
The BCP utility allows you to bulk copy the data from a delimited text file into a SQL Server table.
If you go this approach, things to consider:
Number of Columns in the source file need to match the number of columns in the destination
Data types must match (or be comparable)
Typically, empty strings will be converted to nulls, so you will need to consider if the columns are nullable.
(to name a few - if you want to delve deeper, you might also need to look at custom delimiters between fields and records. Don't forget, commas and line feeds are still valid characters in char type fields).
Anyhow, maybe it will work for you, maybe not. Sure, you might still have to deal with the exporting of the data from Oracle, but it might ease the pain getting the data in.
Have a read:
https://learn.microsoft.com/en-us/sql/tools/bcp-utility?view=sql-server-2017
Why would the TrackedMessages_Copy_BizTalkMsgBoxDb SQL Agent job start failing with "Query processor could not produce a query plan"?
Query processor could not produce a query plan because of the hints defined in this query. Resubmit the query without specifying any hints and without using SET FORCEPLAN. [SQLSTATE 42000] (Error 8622).
Our SQL guys are talking about amending the stored proc. but we've told them to treat BizTalk db's as a black box
It should go without saying, but before anything, make sure to backup your databases. In fact, if your regular backup jobs are running, you may be able to restore a backup and compare things to when it was working on this server. That said -
Check the SQL Agent Job to make sure no additional steps have been added/no plan has been forced/no hints are being used; it should just have one step called 'Purge' that calls the procedure below with the DB server and DTA database name as parameters.
Check the procedure (BizTalkMsgBoxDb.dbo.bts_CopyTrackedMessagesToDTA) to make sure it hasn't been altered.
If this is a production or otherwise sensitive box, back up the DBs and restore them to a local dev environment before proceeding!
If this is not production, see if you can run the procedure (perhaps in a transaction that you rollback) directly in SSMS. See if you get any better errors. Add print statements to see if you can find out exactly where it's getting conflicting hints.
If the procedure won't run, consider freeing the procedure cache (DBCC FREEPROCCACHE) and seeing if the procedure will run.
If it runs in your dev environment from a backup, you may have to start looking at server/database settings. I can't think of which ones off the top of my head that would cause this error though.
For what it's worth, well intentioned DBAs break BizTalk frequently. They decide that an index is missing or not properly covering, or that security could be improved, or that the database should be treated like other databases they administer are treated. I've seen DBAs do really silly things to the BizTalk databases that get very hard to diagnose.
Did you try updating the statistics on the database table referenced by the stored procedure (which is run by the SQL Server Agent job? The query planner uses those to decide how best to execute your SQL.
I have a QML application which user intract with. There is a timer that listen to server for work order then insert all info to SQLite db in application.Also user make change on data (update,delete etc...) in SQLite.
My question is , How to prevent multi operation on SQLite table. Only one operation must take effect on SQLite(select,delete,insert,update....) I don't know but , Can Mutex.lock structure use for this. Or Is there a something wrong with multiple operation on SQLite
First thing you should do is read up on SQLite locking, they have a section in the docs about it: https://www.sqlite.org/lockingv3.html
The summarisation is that SQLite does locking on modifications such as an insert or update, but won't create a lock when reading. However if a lock exists whilst a modification is in progress the read won't be able to access the database.
I wouldn't worry too much about locking on reading, the state should be fine to be shared at that stage.
I want to transfer tables data from SQL server to Informix and vice versa.
The transferring should be run scheduled and sometimes when the user make a specific action.
I do this operation through delete and insert transactions and it takes along long time through the web between 15 minute to 30 minute.
How to do this operation in easy way taking the performance in consideration?
Say I have
Vacation table in SQL Server and want to transfer all the updated data to the Vacation table in Informix.
and
Permission table in Informix and want to transfer all the updated data to the Permission table in SQL Server.
DISCLAIMER: I am not an SQL Server DBA. However, I have been an Informix DBA for over ten years and can make some recommendations as to its performance.
Disclaimer aside, it sounds like you already have a functional application, but the performance is a show-stopper and that is where you are mainly looking for advice.
There are some technical pieces of information that would be helpful to know, but in their absence, I'm going to make the following assumptions about your environment and application. Please comment or edit your question if I am wrong on any of these.
Database server versions. From the tags, it appears you are using SQL server 2012. However, I cannot determine the Informix server and version. I will assume you are running at least IDS 11.50 or greater.
How the data is being exchanged currently. Are you connecting directly from your .NET application to Informix? I would assume that is the case with SQL Server and will make the same assumption for your Informix connection as well.
Table structures. I assume you have proper indexing on the tables. On the Informix side, dbschema -d *dbname* -t *tablename* will give the basic schema.
If you haven't tried exporting data to CSV and as long as you don't have any compliance concerns doing this, I would suggest loading the data from a comma-delimited file. (Informix normally deals with pipe-delimited files, so you'll either need to adjust the delimiter on the SQL Server side to a pipe | or on the Informix import side). On the Informix end, this would be a
LOAD FROM 'source_file_from_sql_server' DELIMITER '|' INSERT INTO vacation (field1, field2, ..)
For reusability, I would recommend putting this in a stored procedure. Just wrap that load statement inside a BEGIN WORK; and COMMIT WORK; to keep your transactional integrity. Michał Niklas suggested some ways to track changes. If there is any correlation between the transfer of data to the vacation table in Informix and the permission table back in SQL Server, I would propose another option, which is adding a trigger to the vacation table so that you write all new values to a staging table.
With the import logic in a stored procedure, you can fire the import on demand:
EXECUTE PROCEDURE vacation_import();
You also mentioned the need to schedule the import, which can be accomplished with Informix's "dbcron". Using this feature, you'll create a scheduled task that executes vacation_import() periodically as well. If you haven't used this feature before, using OAT will be helpful. You will also want to do some housekeeping with the CSV files. This can be addressed with the system() call, which you can make from stored procedures in Informix.
Some ideas:
Add was_transferred column to source tables setting its default value to 0 (you can use 0/1 instead of false/true).
From source table select data with was_transferred=0.
After transferring data update selected source row, set its was_transferred to 1.
Make table syncro_info with fields like date_start and date_stop. If you discover that there is record with date_stop IS NULL it will mean that you are tranferring data. This will protect you against synchronizing data twice.
I have a spark cluster setup and tried both native scala and spark sql on my dataset and the setup seems to work for the most part. I have the following questions
From an ODBC/extenal connectivity to the cluster, what should i expect?
- the admin/developer shapes the data and persists/caches a few RDDs that will be exposed? (Thinking on the lines of hive tables)
- What would be the equivalent of connecting to a "Hive metastore" in spark/spark sql?
Is thinking along the lines of hive faulted?
My other question was
- when i issue hive queries, (and say create tables and such), it uses the same hive metastore as hadoop/hive
- Where do the tables get created when i issue sql queries using sqlcontext?
- If i persist the table, it is the same concept as persisting an RDD?
Appreciate your answers
Nithya
(this is written with spark 1.1 in mind, be aware that new features tend to be added quickly, some limitations mentioned below might very well disappear at some point in the future).
You can use Spark SQL with Hive syntax and connect to Hive metastore, which will result in your Spark SQL hive commands to be executed on the same data space as if they were executed through Hive directly.
To do that you simply need to instantiate a HiveContext as explained here and provide a hive-site.xml configuration file that specifies, among other things, where to find the Hive metastore.
The result of a SELECT statement is a SchemaRDD, which is an RDD of Row objects that has an associated schema. You can use it just like you use any RDD, including cache and persist and the effect is the same (the fact that the data comes from hive has not influence here).
If your hive command is creating data, e.g. "CREATE TABLE ... ", the corresponding table gets created in exactly the same place as with regular Hive, i.e. /var/lib/hive/warehouse by default.
Executing Hive SQL through Spark provides you with all the caching benefits of Spark: executing a 2nd SQL query on the same data set within the same spark context will typically be much faster than the first query.
Since Spark 1.1, it is possible to start the Thrift JDBC server, which is essentially an equivalent to HiveServer2 and thus allows you to execute SparkQL commands through a JDBC connection.
Note that not all Hive features are available (yet?), see details here.
Finally, you can also discard Hive syntax and metastore and execute SQL queries directly on CSV and Parquet files. My best guess is that this will become the preferred approach in the future, although at the moment the set of SQL features available like this is smaller than when using the Hive syntax.