We are facing one issue in our project i.e. Data verification issue.
The project is about Replication of data from Sybase to oracle DBs.
The table structures for Table A across Sybase, Oracle is same.
Same column and primary key combination across all the databases.
e.g. If Sybase has Table A with columns a, b and C
same table with same name and same columns will be available in different databses.
We are done with replication stuff part.But we faced some silent failure like data discrepancy just wondering if there will any tool already available for this.
Any information on his would be helpful. Thanks.
Sybase (now SAP) has a couple products that can be used for data comparisons and reconciliation:
rs_subcmp - an older, 32-bit tool that comes with the Sybase Replication Server product that can be used to compare data between
source and target; SQL reconciliation scripts can be generated from
the differences and then applied to the target to bring it in sync
with the source; if your tables are more than 1GB in size you can
still use rs_subcmp but you'll need to create multiple comparison
jobs (via where clauses) to work on different subsets of your tables
[I don't recall if rs_subcmp can be use for heterogeneous
replication setsup, eg, ASE-Oracle.]
Data Assurance (DA) - the newer, 64-bit product ... also from
Sybase ... which can also compare data and (re)sync the target(s)
from the source (either via SQL reconciliation scripts or directly);
DA is capable of handling comparisons between a handful of
different RDBMS products (eg, ASE-Oracle); I'm currently working on a
project where one of the requirements is to validate (and reconcile
where needed) 200+TB of data being migrated from Oracle to HANA and
I'm using DA for the validation/reconciliation portion of the project
As #TenG has hinted at with his answer, there's a good bit of effort involved to compare data and generate code to reconcile the differences. Rolling your own code is doable but will entail a lot of work. If you've got the money you'll likely find 3rd party tools can get most/all of the work done for you.
If you used a 3rd party product to replicate your data from Sybase to Oracle, you may want to see if the same vendor has a comparison/validation/reconciliation tool you could use.
I've worked on a few migration projects and a key part has always been data reconciliation.
I can only talk about the approaches we took, based on constraints around tools available and minimising downtime, and constraints of available space.
In all cases I took to writing scripts that worked on two levels - summary view and "deep dive". We couldn't find any tools readily available that did what we wanted in a timely enough manner. In fact even the migration tools we found had limitations (datapump, sqlloader, golden gate, etc) and hand coded scripts to handle the bits that we found to be lacking or too slow in the standard tools.
The summary view varied from project to project. It was part functional based (do the accounting figures for transactions match) for the users to verify, and part technical. For smaller tables we could just write simple reports and the diff was straight forward.
For larger tables we wrote technical reports that looked at bands of data (e.g group the PK into 1000s) collect all the column data and produce checksum, generating a report for each table like:
PK ID Range Start Checksum
----------------- -----------
100000 22773377829
200000 38938938282
.
.
Corresponding table pairs from each database were then were "diff"d against each other to highlight discrepancies. Any differences that were found could then be looked at in more detail.
The scripts were written in such a way to allow them to run in parallel looking at discrete bands. Te band ranges were tunable as well to get the best throughput. This obviously sped things up.
The scripts were shell scripts firing off sqlplus reports, and similar for the source database.
On one project there wasn't enough diskspace to do these reports, so I wrote a Java program that queried the two databases side by side, using block queues to fetch and compare rowsets. Being in memory meant this was super fast.
For the "deep dive" we looked at the details for key tables, or for tables that reports a checksum difference.
For the user reports, the users would specify what they wanted to see, and we wrote the reports accordingly.
On the last project, the only discrepancies found were caused by character set conversion issues (people names with accents weren't handled correctly).
On projects where the overall dataset was smaller we extracted the data to XML files and wrote a Java tool to processes pairs and report differences.
The SAP/Sybase rs_subcmp tool is pretty powerful and also pretty hard to use. For details see:
https://help.sap.com/viewer/075940003f1549159206fcc89d020515/16.0.3.3/en-US/feb58db1bd1c1014b134ef4efef25563.html?q=rs_subcmp
You have to pass it key field information, but once you do that, it can retry/restart the compare streams after transient differences. Pretty fancy.
rs_subcmp expects to work on Sybase data source. So to compare against Oracle, you'd probably have to setup one of those Sybase-to-Oracle gateway products ($$$$$).
Could you install the Oracle ODBC drivers and configure them to allow Sybase clients to access Oracle? I'm guessing not (but that's outside the range of my experience).
Note the "-h" option for rs_subcmp. The docs just say it runs a "fast comparison", but what it's actually doing is running queries using the hashbytes() function. Something like:
select keyfield1,keyfield2, hashbytes("Md5",datacol1,datacol2,datacol3)
from mytable
So this sort of query might be good for the "summary view" type comparison discussed above (if the Oracle STANDARD_HASH() function output matches up with the Sybase hashbytes() function (again, outside my experience))
Note, as of ASE 16, there was a bug with the hash() & hashbytes() functions running the Md5 hash option against large varbinary columns where they could use up all procedure cache, potentially crashing the server (CR 811073)
Related
I’m in the middle of trying to migrate a large amount of data into a oracle database from existing excel-files.
Due to the large amount of rows loaded (10 000 and more) every time, it is not possible to use SQL Developer for this tasks.
In every work-sheet there’s data that need to go into different tables, but at the same time keep the relations and not dropping any data.
As for now, I use one .CSV file for each table and mapping them together afterwards. This is thou combined with a great risk of adding the wrong FK and with that screw up the hole shit. And I don’t have the time, energy or will for clean ups even if it is my own mess…
My initial thought was if I could bulk transfer with sql loader using some kind of plsql-script in maybe an ctl-file (the used for mapping the properties) but it seems like I.m quite out in the bush with that one… (or am I…? )
The other thought was to create a simple program In c# and use fastMember and load the database that way. (But that means that I need to take the time to actually make the program, however small it is).
I can’t possible be the only one that have had this issue, but trying to us my notToElevatedNinjaGoogling-skills ends up with either using sql developer (witch is not an alternative) or the bulk copy thing from sql load (and where I need to map it all together afterwards).
Is there any alternative solutions for my problem or is the above solutions the one that I need to cope with?
Did you consider using CSV files as external tables? As they act as if they were ordinary Oracle tables, you can write (PL/)SQL against them, inserting data into different tables in the target schema. That might give you some more freedom & control over what you are doing.
Behind the scene, it is still SQL*Loader.
It's kinda real-world problem and I believe the solution exists but couldn't find one.
So We, have a Database called Transactions that contains tables such as Positions, Securities, Bogies, Accounts, Commodities and so on being updated continuously every second whenever a new transaction happens. For the time being, We have replicated master database Transaction to a new database with name TRN on which we do all the querying and updating stuff.
We want a sort of monitoring system ( like htop process viewer in Linux) for Database that dynamically lists updated rows in tables of the database at any time.
TL;DR Is there any way to get a continuous updating list of rows in any table in the database?
Currently we are working on Sybase & Oracle DBMS on Linux (Ubuntu) platform but we would like to receive generic answers that concern most of the platform as well as DBMS's(including MySQL) and any tools, utilities or scripts that can do so that It can help us in future to easily migrate to other platforms and or DBMS as well.
To list updated rows, you conceptually need either of the two things:
The updating statement's effect on the table.
A previous version of the table to compare with.
How you get them and in what form is completely up to you.
The 1st option allows you to list updates with statement granularity while the 2nd is more suitable for time-based granularity.
Some options from the top of my head:
Write to a temporary table
Add a field with transaction id/timestamp
Make clones of the table regularly
AFAICS, Oracle doesn't have built-in facilities to get the affected rows, only their count.
Not a lot of details in the question so not sure how much of this will be of use ...
'Sybase' is mentioned but nothing is said about which Sybase RDBMS product (ASE? SQLAnywhere? IQ? Advantage?)
by 'replicated master database transaction' I'm assuming this means the primary database is being replicated (as opposed to the database called 'master' in a Sybase ASE instance)
no mention is made of what products/tools are being used to 'replicate' the transactions to the 'new database' named 'TRN'
So, assuming part of your environment includes Sybase(SAP) ASE ...
MDA tables can be used to capture counters of DML operations (eg, insert/update/delete) over a given time period
MDA tables can capture some SQL text, though the volume/quality could be in doubt if a) MDA is not configured properly and/or b) the DML operations are wrapped up in prepared statements, stored procs and triggers
auditing could be enabled to capture some commands but again, volume/quality could be in doubt based on how the DML commands are executed
also keep in mind that there's a performance hit for using MDA tables and/or auditing, with the level of performance degradation based on individual config settings and the volume of DML activity
Assuming you're using the Sybase(SAP) Replication Server product, those replicated transactions sent through repserver likely have all the info you need to know which tables/rows are being affected; so you have a couple options:
route a copy of the transactions to another database where you can capture the transactions in whatever format you need [you'll need to design the database and/or any customized repserver function strings]
consider using the Sybase(SAP) Real Time Data Streaming product (yeah, additional li$ence is required) which is specifically designed for scenarios like yours, ie, pull transactions off the repserver queues and format for use in downstream systems (eg, tibco/mqs, custom apps)
I'm not aware of any 'generic' products that work, out of the box, as per your (limited) requirements. You're likely looking at some different solutions and/or customized code to cover your particular situation.
We are planning a new system for a client in ORACLE 11g. I've been mostly in the Sql Server world for several years, and am not really current on the latest ORACLE updates.
One particular feature I'm wondering if ORACLE has added in by this point is some sort of logical "container" for database objects, akin to Sql Server's SCHEMA.
Trying to use ORACLE's schemas like Sql Server winds up being a disaster for code comparisons when trying to push from dev > test > live.
Packages are sort of similar, except that you can't put tables into a package (so they really only work for logical code grouping).
The only other option I am aware of is the archaic practice of having to prefix object names with a "schema" prefix, i.e. RPT_REPORTS, RPT_PARAMETERS, RPT_LOGS, RPT_USERS, RPT_RUN_REPORT(), with the prefix RPT_ denoting that these are all the objects dealing with our reporting engine say. Writing a system like this feels like we never left the 8.3 file-naming age.
Is there by this point in time any cleaner, more direct way of logically grouping related objects together in ORACLE?
Oracle's logical container for database objects IS the schema. I don't know how much "cleaner" and "more direct" you can get! You are going to have to do a paradigm shift here. Don't try to think in SQL Server terms, and force a solution that looks like SQL Server on Oracle. Get familiar with what Oracle does and approach your problems from that perspective. There should be no problem pushing from dev to test to production in Oracle if you know what you're doing.
It seems you have a bit of a chip on your shoulder about Oracle when you use terms like "archaic practice". I would suggest you make friends with Oracle's very rich and powerful feature set by doing some reading, since you're apparently already committed to Oracle for this project. In particular, pick up a copy of "Effective Oracle By Design" by Tom Kyte. Once you've read that, have a look at "Expert Oracle Database Architecture" by the same author for a more in-depth look at how Oracle works. You owe it to your customer to know how to use the tool you've been handed. Who knows? You might even start to like it. Think of it as another tool in your toolchest. You're not married to SQL Server and you're not being unfaithful by using Oracle ;-)
EDIT:
In response to questions by OP:
I'm not sure why that is a logistical problem. They can be thought of as separate databases, but physically they are not. And no, you do not need a separate data file for each schema. A single datafile is often used for all schemas.
If you want a "nice, self-contained database" ala SQL Server, just create one schema to store all your objects. End of problem. You can create other users/schemas, just don't give them the ability to create objects.
There are tools to compare objects and data, as in the PL/SQL Developer compare. Typically in Oracle you want to compare schemas, not entire databases. I'm not sure why it is you want to have multiple schemas each with their own objects anyway. What does is buy you to do that? Keep your objects (tables, triggers, code, views, etc.) in one schema.
Looking for a bit of advice on how to optimise one of our projects. We have a ASP.NET/C# system that retrieves data from a SQL2008 data and presents it on a DevExpress ASPxGridView. The data that's retrieved can come from one of a number of databases - all of which are slightly different and are being added and removed regularly. The user is presented with a list of live "companies", and the data is retrieved from the corresponding database.
At the moment, data is being retrieved using a standard SqlDataSource and a dynamically-created SQL SELECT statement. There are a few JOINs in the statement, as well as optional WHERE constraints, again dynamically-created depending on the database and the user's permission level.
All of this works great (honest!), apart from performance. When it comes to some databases, there are several hundreds of thousands of rows, and retrieving and paging through the data is quite slow (the databases are already properly indexed). I've therefore been looking at ways of speeding the system up, and it seems to boil down to two choices: XPO or LINQ.
LINQ seems to be the popular choice, but I'm not sure how easy it will be to implement with a system that is so dynamic in nature - would I need to create "definitions" for each database that LINQ could access? I'm also a bit unsure about creating the LINQ queries dynamically too, although looking at a few examples that part at least seems doable.
XPO, on the other hand, seems to allow me to create a XPO Data Source on the fly. However, I can't find too much information on how to JOIN to other tables.
Can anyone offer any advice on which method - if any - is the best to try and retro-fit into this project? Or is the dynamic SQL model currently used fundamentally different from LINQ and XPO and best left alone?
Before you go and change the whole way that your app talks to the database, have you had a look at the following:
Run your code through a performance profiler (such as Redgate's performance profiler), the results are often surprising.
If you are constructing the SQL string on the fly, are you using .Net best practices such as String.Concat("str1", "str2") instead of "str1" + "str2". Remember, multiple small gains add up to big gains.
Have you thought about having a summary table or database that is periodically updated (say every 15 mins, you might need to run a service to update this data automatically.) so that you are only hitting one database. New connections to databases are quiet expensive.
Have you looked at the query plans for the SQL that you are running. Today, I moved a dynamically created SQL string to a sproc (only 1 param changed) and shaved 5-10 seconds off the running time (it was being called 100-10000 times depending on some conditions).
Just a warning if you do use LINQ. I have seen some developers who have decided to use LINQ write more inefficient code because they did not know what they are doing (pulling 36,000 records when they needed to check for 1 for example). This things are very easily overlooked.
Just something to get you started on and hopefully there is something there that you haven't thought of.
Cheers,
Stu
As far as I understand you are talking about so called server mode when all data manipulations are done on the DB server instead of them to the web server and processing them there. In this mode grid works very fast with data sources that can contain hundreds thousands records. If you want to use this mode, you should either create the corresponding LINQ classes or XPO classes. If you decide to use LINQ based server mode, the LINQServerModeDataSource provides the Selecting event which can be used to set a custom IQueryable and KeyExpression. I would suggest that you use LINQ in your application. I hope, this information will be helpful to you.
I guess there are two points where performance might be tweaked in this case. I'll assume that you're accessing the database directly rather than through some kind of secondary layer.
First, you don't say how you're displaying the data itself. If you're loading thousands of records into a grid, that will take time no matter how fast everything else is. Obviously the trick here is to show a subset of the data and allow the user to page, etc. If you're not doing this then that might be a good place to start.
Second, you say that the tables are properly indexed. If this is the case, and assuming that you're not loading 1,000 records into the page at once and retreiving only subsets at a time, then you should be OK.
But, if you're only doing an ExecuteQuery() against an SQL connection to get a dataset back I don't see how Linq or anything else will help you. I'd say that the problem is obviously on the DB side.
So to solve the problem with the database you need to profile the different SELECT statements you're running against it, examine the query plan and identify the places where things are slowing down. You might want to start by using the SQL Server Profiler, but if you have a good DBA, sometimes just looking at the query plan (which you can get from Management Studio) is usually enough.
I need to store large amount of small data objects (millions of rows per month). Once they're saved they wont change. I need to :
store them securely
use them to analysis (mostly time-oriented)
retrieve some raw data occasionally
It would be nice if it could be used with JasperReports or BIRT
My first shot was Infobright Community - just a column-oriented, read-only storing mechanism for MySQL
On the other hand, people says that NoSQL approach could be better. Hadoop+Hive looks promissing, but the documentation looks poor and the version number is less than 1.0 .
I heard about Hypertable, Pentaho, MongoDB ....
Do you have any recommendations ?
(Yes, I found some topics here, but it was year or two ago)
Edit:
Other solutions : MonetDB, InfiniDB, LucidDB - what do you think?
Am having the same problem here and made researches; two types of storages for BI :
column oriented. Free and known : monetDB, LucidDb, Infobright. InfiniDB
Distributed : hTable, Cassandra (also column oriented theoretically)
Document oriented / MongoDb, CouchDB
The answer depends on what you really need :
If your millions of row are loaded at once (nighly batch or so), InfiniDB or other column oriented DB are the best; They have great performance and are "BI oriented". http://www.d1solutions.ch/papers/d1_2010_hauenstein_real_life_performance_database.pdf
And they won't require a setup of "nodes", "sharding" and other stuff that comes with distributed/"NoSQL" DBs.
http://www.mysqlperformanceblog.com/2010/01/07/star-schema-bechmark-infobright-infinidb-and-luciddb/
If the rows are added in real time.. then column oriented DB are bad. You can either choose two have two separate DB (that's my choice : one noSQL for real feeding of the stats by the front, and real time stats. The other DB column-oriented for BI). Or turn towards something that mixes column oriented (for out requests) and distribution (for writes) / like Cassandra.
Document oriented DBs are not suited for BI, they are more useful for CRM/CMS issues where you need frequent access to a particular row
As for the exact choice inside a category, I'm still undecided. Cassandra in distributed, and Monet or InfiniDB for CODB, are leaders. Monet is reported to have problem loading very big tables because it runs indexes in memory.
You could also consider GridSQL. Even for a single server, you can create multiple logical "nodes" to utilize multiple cores when processing queries.
GridSQL uses PostgreSQL, so you can also take advantage of partitioning tables into subtables to evaluate queries faster. You mentioned the data is time-oriented, so that would be a good candidate for creating subtables.
If you're looking for compatibility with reporting tools, something based on MySQL may be your best choice. As for what will work for you, Infobright may work. There are several other solutions as well, however you may want also to look at plain-old MySQL and the Archive table. Each record is compressed and stored and, IIRC, it's designed for your type of workload, however I think Infobright is supposed to get better compression. I haven't really used either, so I'm not sure which will work best for you.
As for the key-value stores (E.g. NoSQL), yes, they can work as well and there are plenty of alternatives out there. I know CouchDB has "views", but I haven't had the opportunity to use any, so I don't know how well any of them work.
My only concern with your data set is that since you mentioned time, you may want to ensure that whatever solution you use will allow you to archive data past a certain time. It's a common data warehouse practice to only keep N months of data online and archive the rest. This is where partitioning, as implemented in an RDBMS, comes in very useful.