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  • Return more then One field from database SQLAlchemy

    - by David Neudorfer
    This line: used_emails = [row.email for row in db.execute(select([halo4.c.email], halo4.c.email!=''))] Returns: ['[email protected]', '[email protected]', '[email protected]', '[email protected]', '[email protected]'] I use this to find a match: if recipient in used_emails: If it finds a match I need to pull another field (halo4.c.code) from the database in the same row. Any suggestions on how to do this?

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  • Using SQLAlchemy, how can I return a count with multiple columns

    - by Andy
    I am attempting to run a query like this: SELECT comment_type_id, name, count(comment_type_id) FROM comments, commenttypes WHERE comment_type_id=commenttypes.id GROUP BY comment_type_id Without the join between comments and commenttypes for the name column, I can do this using: session.query(Comment.comment_type_id,func.count(Comment.comment_type_id)).group_by(Comment.comment_type_id).all() However, if I try to do something like this, I get incorrect results: session.query(Comment.comment_type_id, Comment.comment_type, func.count(Comment.comment_type_id)).group_by(Comment.comment_type_id).all() I have two problems with the results: (1, False, 82920) (2, False, 588) (3, False, 4278) (4, False, 104370) Problems: The False is not correct The counts are wrong My expected results are: (1, 'Comment Type 1', 13820) (2, 'Comment Type 2', 98) (3, 'Comment Type 2', 713) (4, 'Comment Type 2', 17395) How can I adjust my command to pull the correct name value and the correct count?

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  • sqlalchemy natural sorting

    - by teggy
    Currently, i am querying with this code: meta.Session.query(Label).order_by(Label.name).all() and it returns me objects sorted by Label.name in this manner ['1','7','1a','5c']. Is there a way i can have the objects returned in the order with their Label.name sorted like this ['1','1a','5c','7'] Thanks!

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  • How to map one class against multiple tables with SQLAlchemy?

    - by tote
    Lets say that I have a database structure with three tables that look like this: items - item_id - item_handle attributes - attribute_id - attribute_name item_attributes - item_attribute_id - item_id - attribute_id - attribute_value I would like to be able to do this in SQLAlchemy: item = Item('item1') item.foo = 'bar' session.add(item) session.commit() item1 = session.query(Item).filter_by(handle='item1').one() print item1.foo # => 'bar' I'm new to SQLAlchemy and I found this in the documentation (http://www.sqlalchemy.org/docs/05/mappers.html#mapping-a-class-against-multiple-tables): j = join(items, item_attributes, items.c.item_id == item_attributes.c.item_id). \ join(attributes, item_attributes.c.attribute_id == attributes.c.attribute_id) mapper(Item, j, properties={ 'item_id': [items.c.item_id, item_attributes.c.item_id], 'attribute_id': [item_attributes.c.attribute_id, attributes.c.attribute_id], }) It only adds item_id and attribute_id to Item and its not possible to add attributes to Item object. Is what I'm trying to achieve possible with SQLAlchemy? Is there a better way to structure the database to get the same behaviour of "dynamic columns"?

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  • Filtering SQLAlchemy query on attribute_mapped_collection field of relationship

    - by bsa
    I have two classes, Tag and Hardware, defined with a simple parent-child relationship (see the full definition at the end). Now I want to filter a query on Tag using the version field in Hardware through an attribute_mapped_collection, eg: def get_tags(order_code=None, hardware_filters=None): session = Session() query = session.query(Tag) if order_code: query = query.filter(Tag.order_code == order_code) if hardware_filters: for k, v in hardware_filters.iteritems(): query = query.filter(getattr(Tag.hardware, k).version == v) return query.all() But I get: AttributeError: Neither 'InstrumentedAttribute' object nor 'Comparator' object associated with Tag.hardware has an attribute 'baseband The same thing happens if I strip it back by hard-coding the attribute, eg: query.filter(Tag.hardware.baseband.version == v) I can do it this way: query = query.filter(Tag.hardware.any(artefact=k, version=v)) But why can't I filter directly through the attribute? Class definitions class Tag(Base): __tablename__ = 'tag' tag_id = Column(Integer, primary_key=True) order_code = Column(String, nullable=False) version = Column(String, nullable=False) status = Column(String, nullable=False) comments = Column(String) hardware = relationship( "Hardware", backref="tag", collection_class=attribute_mapped_collection('artefact'), ) __table_args__ = ( UniqueConstraint('order_code', 'version'), ) class Hardware(Base): __tablename__ = 'hardware' hardware_id = Column(Integer, primary_key=True) tag_id = Column(String, ForeignKey('tag.tag_id')) product_id = Column(String, nullable=True) artefact = Column(String, nullable=False) version = Column(String, nullable=False)

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  • migrate from jdk 14 to jdk 16

    - by Padur
    soon we are moving from jdk14 and start using jdk16.Ours is desktop application. What measures I need to take to make sure it works correctly on clients machine? Right now some of them using JRE4 and some JRE6.Server- Solaris. PD

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  • Migrate 12.04 Wubi install to new partition with corrupted win7 install and small hard drive

    - by Robin Clark
    The move from Win7 to Ubuntu 12.04 has been honestly awesome. But I've come into a snag because my Win7 inevitably broke. I can still boot into Ubuntu even though Win7 is broken (won't boot, can't repair). I'd like to Migrate Wubi to a real partition and forget about windows. Presumably under normal conditions I would run the Ubuntu live CD, create a new partition then log back into my Wubi install and migrate using the script to the new partition. But I'm worried if I do that I'll break my current wubi set-up and be unable to migrate. I have a small hard drive, only 75GB and unfortunately my backup drive recently died so can't migrate there first and transfer over either. Does anybody have any suggestions to solve this?

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  • How to use SQLAlchemy to dump an SQL file from query expressions to bulk-insert into a DBMS?

    - by Mahmoud Abdelkader
    Please bear with me as I explain the problem, how I tried to solve it, and my question on how to improve it is at the end. I have a 100,000 line csv file from an offline batch job and I needed to insert it into the database as its proper models. Ordinarily, if this is a fairly straight-forward load, this can be trivially loaded by just munging the CSV file to fit a schema, but I had to do some external processing that requires querying and it's just much more convenient to use SQLAlchemy to generate the data I want. The data I want here is 3 models that represent 3 pre-exiting tables in the database and each subsequent model depends on the previous model. For example: Model C --> Foreign Key --> Model B --> Foreign Key --> Model A So, the models must be inserted in the order A, B, and C. I came up with a producer/consumer approach: - instantiate a multiprocessing.Process which contains a threadpool of 50 persister threads that have a threadlocal connection to a database - read a line from the file using the csv DictReader - enqueue the dictionary to the process, where each thread creates the appropriate models by querying the right values and each thread persists the models in the appropriate order This was faster than a non-threaded read/persist but it is way slower than bulk-loading a file into the database. The job finished persisting after about 45 minutes. For fun, I decided to write it in SQL statements, it took 5 minutes. Writing the SQL statements took me a couple of hours, though. So my question is, could I have used a faster method to insert rows using SQLAlchemy? As I understand it, SQLAlchemy is not designed for bulk insert operations, so this is less than ideal. This follows to my question, is there a way to generate the SQL statements using SQLAlchemy, throw them in a file, and then just use a bulk-load into the database? I know about str(model_object) but it does not show the interpolated values. I would appreciate any guidance for how to do this faster. Thanks!

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  • How to create and restore a backup from SqlAlchemy?

    - by swilliams
    I'm writing a Pylons app, and am trying to create a simple backup system where every table is serialized and tarred up into a single file for an administrator to download, and use to restore the app should something bad happen. I can serialize my table data just fine using the SqlAlchemy serializer, and I can deserialize it fine as well, but I can't figure out how to commit those changes back to the database. In order to serialize my data I am doing this: from myproject.model.meta import Session from sqlalchemy.ext.serializer import loads, dumps q = Session.query(MyTable) serialized_data = dumps(q.all()) In order to test things out, I go ahead and truncation MyTable, and then attempt to restore using serialized_data: from myproject.model import meta restore_q = loads(serialized_data, meta.metadata, Session) This doesn't seem to do anything... I've tried calling a Session.commit after the fact, individually walking through all the objects in restore_q and adding them, but nothing seems to work. What am I missing? Or is there a better way to do what I'm aiming for? I don't want to shell out and directly touch the database, since SqlAlchemy supports different database engines.

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  • Shortcut for rake db:migrate:down for ruby-on-rails

    - by Michaël
    Hi, I want to know if there is a short way to do the migrations down equivalent to rake db:migrate (for the migrations up). Instead of doing : rake db:migrate:up VERSION=1, rake db:migrate:up VERSION=2, ... we can do : rake db:migrate! But for : rake db:migrate:down VERSION=10, rake db:migrate:down VERSION=..., rake db:migrate:down VERSION=1, is there a shortcut? Tank you for your help!

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  • How to set up global connect to datebase in pylons(python), sqlalchemy.

    - by gummmibear
    Hi! I just start lern python, pylons. i have problem with setting up datebase connection. i won't to set connection, where i can see this connection in all my controllers. Now i use: some thing like this in my controller: 45 ' db = create_engine('mysql://root:password@localhost/python') 46 ' metadata = MetaData(db) 47 48 ' email_list = Table('email',metadata,autoload=True) in development.ini i have: 44 sqlalchemy.url = mysql://root@password@localhost/python 45 sqlalchemy.pool_recycle = 3600 and now, pleas help me to set __init__.py

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  • Upgrading a hard disk – To repave or to migrate, that is the question

    - by guybarrette
    I recently changed my laptop hard disk from the stock 250GB 5400 drive to a 320GB 7200 drive.  And no, I didn’t bought a SSD drive because the cost is way too much right now.  At $70, my upgrade was a lot cheaper than a SSD drive.  Maybe next year. When changing a system main hard drive, one must ask himself: To repave or to migrate, that is the question.  I choose to migrate so I went to the Acronis Website to take a look at their product line.  They have a few products that could do the job.  One being Acronis Migrate Easy 7.0 and the other being Acronis True Image Home 2010.  Since True Image was just $10 more then Migrate Easy, I bought True Image. I inserted my new hard drive in a 2.5” USB enclosure, and started the migration process.  Once the data copied, I switched the drives.  The process went very smoothly and without hiccups.  Highly recommended. BTW, Acronis offers free trials so I guess that nothing can stop you from “testing” a migration  ;-) var addthis_pub="guybarrette";

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  • Using SQL Alchemy and pyodbc with IronPython 2.6.1

    - by beargle
    I'm using IronPython and the clr module to retrieve SQL Server information via SMO. I'd like to retrieve/store this data in a SQL Server database using SQL Alchemy, but am having some trouble loading the pyodbc module. Here's the setup: IronPython 2.6.1 (installed at D:\Program Files\IronPython) CPython 2.6.5 (installed at D:\Python26) SQL Alchemy 0.6.1 (installed at D:\Python26\Lib\site-packages\sqlalchemy) pyodbc 2.1.7 (installed at D:\Python26\Lib\site-packages) I have these entries in the IronPython site.py to import CPython standard and third-party libraries: # Add CPython standard libs and DLLs import sys sys.path.append(r"D:\Python26\Lib") sys.path.append(r"D:\Python26\DLLs") sys.path.append(r"D:\Python26\lib-tk") sys.path.append(r"D:\Python26") # Add CPython third-party libs sys.path.append(r"D:\Python26\Lib\site-packages") # sqlite3 sys.path.append(r"D:\Python26\Lib\sqlite3") # Add SQL Server SMO sys.path.append(r"D:\Program Files\Microsoft SQL Server\100\SDK\Assemblies") import clr clr.AddReferenceToFile('Microsoft.SqlServer.Smo.dll') clr.AddReferenceToFile('Microsoft.SqlServer.SqlEnum.dll') clr.AddReferenceToFile('Microsoft.SqlServer.ConnectionInfo.dll') SQL Alchemy imports OK in IronPython, put I receive this error message when trying to connect to SQL Server: IronPython 2.6.1 (2.6.10920.0) on .NET 2.0.50727.3607 Type "help", "copyright", "credits" or "license" for more information. >>> import sqlalchemy >>> e = sqlalchemy.MetaData("mssql://") Traceback (most recent call last): File "<stdin>", line 1, in <module> File "D:\Python26\Lib\site-packages\sqlalchemy\schema.py", line 1780, in __init__ File "D:\Python26\Lib\site-packages\sqlalchemy\schema.py", line 1828, in _bind_to File "D:\Python26\Lib\site-packages\sqlalchemy\engine\__init__.py", line 241, in create_engine File "D:\Python26\Lib\site-packages\sqlalchemy\engine\strategies.py", line 60, in create File "D:\Python26\Lib\site-packages\sqlalchemy\connectors\pyodbc.py", line 29, in dbapi ImportError: No module named pyodbc This code works just fine in CPython, but it looks like the pyodbc module isn't accessible from IronPython. Any suggestions? I realize that this may not be the best way to approach the problem, so I'm open to tackling this a different way. Just wanted to get some experience with using SQL Alchemy and pyodbc.

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  • How to migrate exchange 2007 (sherweb) to Google Apps?

    - by Yoffe
    I need to migrate our Sherweb.com exchange 2007 services to a Google Apps account. For the process I am really not sure.. I understand I should start with creating aliases for all email accounts within the exchange server, in Google Apps, and here I'm not sure how am I supposed to explain the Exchange that the DNS have changed without losing emails.'' Second thing is: How can I safely move the up-to 3GB mailboxes from the Exchange server to the new Google Apps accounts? Must it be with Outlook data files? If so, how do I actually upload the data files into the Google Apps account? And if not, what would be a proper way to do so? Would really appreciate any kind of help.

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  • Is there a rake task for advancing or retreating your schema version by exactly one?

    - by user30997
    Back when migration version numbers were simply incremented as you created migrations, it was easy enough to do: rake migrate VERSION=097 rake migrate VERSION=098 rake migrate VERSION=099 rake migrate VERSION=100 ...but we now have migration numbers that are something like YYYYMMDDtimeofday. Not that this is a bad thing - it keeps the migration version collisions to a minimum - but when I have 50 migrations and want to step through them one-at-a-time, it is a hassle: rake migrate VERSION=20090129215142 rake migrate VERSION=20090129219783 ...etc. I have to have a list of all the migrations open in front of me, typing out the version numbers to advance by one. Is there anything that would have an easier syntax, like: rake migrate VERSION=NEXT or rake migrate VERSION=PREV ?

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  • How do I join three tables with SQLalchemy and keeping all of the columns in one of the tables?

    - by jimka
    So, I have three tables: The class defenitions: engine = create_engine('sqlite://test.db', echo=False) SQLSession = sessionmaker(bind=engine) Base = declarative_base() class Channel(Base): __tablename__ = 'channel' id = Column(Integer, primary_key = True) title = Column(String) description = Column(String) link = Column(String) pubDate = Column(DateTime) class User(Base): __tablename__ = 'user' id = Column(Integer, primary_key = True) username = Column(String) password = Column(String) sessionId = Column(String) class Subscription(Base): __tablename__ = 'subscription' userId = Column(Integer, ForeignKey('user.id'), primary_key=True) channelId = Column(Integer, ForeignKey('channel.id'), primary_key=True) And the SQL commands that are executed to create them: CREATE TABLE subscription ( "userId" INTEGER NOT NULL, "channelId" INTEGER NOT NULL, PRIMARY KEY ("userId", "channelId"), FOREIGN KEY("userId") REFERENCES user (id), FOREIGN KEY("channelId") REFERENCES channel (id) ); CREATE TABLE user ( id INTEGER NOT NULL, username VARCHAR, password VARCHAR, "sessionId" VARCHAR, PRIMARY KEY (id) ); CREATE TABLE channel ( id INTEGER NOT NULL, title VARCHAR, description VARCHAR, link VARCHAR, "pubDate" TIMESTAMP, PRIMARY KEY (id) ); NOTE: I know user.username should be unique, need to fix that, and I'm not sure why SQLalchemy creates some row names with the double-quotes. And I'm trying to come up with a way to retrieve all of the channels, as well as an indication on what channels one particular user (identified by user.sessionId together with user.id) has a subscription on. For example, say we have four channels: channel1, channel2, channel3, channel4; a user: user1; who has a subscription on channel1 and channel4. The query for user1 would return something like: channel.id | channel.title | subscribed --------------------------------------- 1 channel1 True 2 channel2 False 3 channel3 False 4 channel4 True This is a best-case result, but since I have absolutely no clue as how to accomplish the subscribed column, I've been instead trying to get the particular users id in the rows where the user has a subscription and where a subscription is missing, just leave it blank. The database engine that I'm using together with SQLalchemy atm. is sqlite3 I've been scratching my head over this for two days now, I've no problem joining together all three by way of the subscription table but then all of the channels where the user does not have a subscription gets omitted. I hope I've managed to describe my problem sufficiently, thanks in advance.

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  • Use a foreign key mapping to get data from the other table using Python and SQLAlchemy.

    - by Az
    Hmm, the title was harder to formulate than I thought. Basically, I've got these simple classes mapped to tables, using SQLAlchemy. I know they're missing a few items but those aren't essential for highlighting the problem. class Customer(object): def __init__(self, uid, name, email): self.uid = uid self.name = name self.email = email def __repr__(self): return str(self) def __str__(self): return "Cust: %s, Name: %s (Email: %s)" %(self.uid, self.name, self.email) The above is basically a simple customer with an id, name and an email address. class Order(object): def __init__(self, item_id, item_name, customer): self.item_id = item_id self.item_name = item_name self.customer = None def __repr__(self): return str(self) def __str__(self): return "Item ID %s: %s, has been ordered by customer no. %s" %(self.item_id, self.item_name, self.customer) This is the Orders class that just holds the order information: an id, a name and a reference to a customer. It's initialised to None to indicate that this item doesn't have a customer yet. The code's job will assign the item a customer. The following code maps these classes to respective database tables. # SQLAlchemy database transmutation engine = create_engine('sqlite:///:memory:', echo=False) metadata = MetaData() customers_table = Table('customers', metadata, Column('uid', Integer, primary_key=True), Column('name', String), Column('email', String) ) orders_table = Table('orders', metadata, Column('item_id', Integer, primary_key=True), Column('item_name', String), Column('customer', Integer, ForeignKey('customers.uid')) ) metadata.create_all(engine) mapper(Customer, customers_table) mapper(Orders, orders_table) Now if I do something like: for order in session.query(Order): print order I can get a list of orders in this form: Item ID 1001: MX4000 Laser Mouse, has been ordered by customer no. 12 What I want to do is find out customer 12's name and email address (which is why I used the ForeignKey into the Customer table). How would I go about it?

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  • Is it possible in SQLAlchemy to filter by a database function or stored procedure?

    - by Rico Suave
    We're using SQLalchemy in a project with a legacy database. The database has functions/stored procedures. In the past we used raw SQL and we could use these functions as filters in our queries. I would like to do the same for SQLAlchemy queries if possible. I have read about the @hybrid_property, but some of these functions need one or more parameters, for example; I have a User model that has a JOIN to a bunch of historical records. These historical records for this user, have a date and a debit and credit field, so we can look up the balance of a user at a specific point in time, by doing a SUM(credit) - SUM(debit) up until the given date. We have a database function for that called dbo.Balance(user_id, date_time). I can use this to check the balance of a user at a given point in time. I would like to use this as a criterium in a query, to select only users that have a negative balance at a specific date/time. selection = users.filter(coalesce(Users.status, 0) == 1, coalesce(Users.no_reminders, 0) == 0, dbo.pplBalance(Users.user_id, datetime.datetime.now()) < -0.01).all() This is of course a non-working example, just for you to get the gist of what I'd like to do. The solution looks to be to use hybrd properties, but as I mentioned above, these only work without parameters (as they are properties, not methods). Any suggestions on how to implement something like this (if it's even possible) are welcome. Thanks,

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  • SQL – Migrate Database from SQL Server to NuoDB – A Quick Tutorial

    - by Pinal Dave
    Data is growing exponentially and every organization with growing data is thinking of next big innovation in the world of Big Data. Big data is a indeed a future for every organization at one point of the time. Just like every other next big thing, big data has its own challenges and issues. The biggest challenge associated with the big data is to find the ideal platform which supports the scalability and growth of the data. If you are a regular reader of this blog, you must be familiar with NuoDB. I have been working with NuoDB for a while and their recent release is the best thus far. NuoDB is an elastically scalable SQL database that can run on local host, datacenter and cloud-based resources. A key feature of the product is that it does not require sharding (read more here). Last week, I was able to install NuoDB in less than 90 seconds and have explored their Explorer and Admin sections. You can read about my experiences in these posts: SQL – Step by Step Guide to Download and Install NuoDB – Getting Started with NuoDB SQL – Quick Start with Admin Sections of NuoDB – Manage NuoDB Database SQL – Quick Start with Explorer Sections of NuoDB – Query NuoDB Database Many SQL Authority readers have been following me in my journey to evaluate NuoDB. One of the frequently asked questions I’ve received from you is if there is any way to migrate data from SQL Server to NuoDB. The fact is that there is indeed a way to do so and NuoDB provides a fantastic tool which can help users to do it. NuoDB Migrator is a command line utility that supports the migration of Microsoft SQL Server, MySQL, Oracle, and PostgreSQL schemas and data to NuoDB. The migration to NuoDB is a three-step process: NuoDB Migrator generates a schema for a target NuoDB database It loads data into the target NuoDB database It dumps data from the source database Let’s see how we can migrate our data from SQL Server to NuoDB using a simple three-step approach. But before we do that we will create a sample database in MSSQL and later we will migrate the same database to NuoDB: Setup Step 1: Build a sample data CREATE DATABASE [Test]; CREATE TABLE [Department]( [DepartmentID] [smallint] NOT NULL, [Name] VARCHAR(100) NOT NULL, [GroupName] VARCHAR(100) NOT NULL, [ModifiedDate] [datetime] NOT NULL, CONSTRAINT [PK_Department_DepartmentID] PRIMARY KEY CLUSTERED ( [DepartmentID] ASC ) ) ON [PRIMARY]; INSERT INTO Department SELECT * FROM AdventureWorks2012.HumanResources.Department; Note that I am using the SQL Server AdventureWorks database to build this sample table but you can build this sample table any way you prefer. Setup Step 2: Install Java 64 bit Before you can begin the migration process to NuoDB, make sure you have 64-bit Java installed on your computer. This is due to the fact that the NuoDB Migrator tool is built in Java. You can download 64-bit Java for Windows, Mac OSX, or Linux from the following link: http://java.com/en/download/manual.jsp. One more thing to remember is that you make sure that the path in your environment settings is set to your JAVA_HOME directory or else the tool will not work. Here is how you can do it: Go to My Computer >> Right Click >> Select Properties >> Click on Advanced System Settings >> Click on Environment Variables >> Click on New and enter the following values. Variable Name: JAVA_HOME Variable Value: C:\Program Files\Java\jre7 Make sure you enter your Java installation directory in the Variable Value field. Setup Step 3: Install JDBC driver for SQL Server. There are two JDBC drivers available for SQL Server.  Select the one you prefer to use by following one of the two links below: Microsoft JDBC Driver jTDS JDBC Driver In this example we will be using jTDS JDBC driver. Once you download the driver, move the driver to your NuoDB installation folder. In my case, I have moved the JAR file of the driver into the C:\Program Files\NuoDB\tools\migrator\jar folder as this is my NuoDB installation directory. Now we are all set to start the three-step migration process from SQL Server to NuoDB: Migration Step 1: NuoDB Schema Generation Here is the command I use to generate a schema of my SQL Server Database in NuoDB. First I go to the folder C:\Program Files\NuoDB\tools\migrator\bin and execute the nuodb-migrator.bat file. Note that my database name is ‘test’. Additionally my username and password is also ‘test’. You can see that my SQL Server database is running on my localhost on port 1433. Additionally, the schema of the table is ‘dbo’. nuodb-migrator schema –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.path=/tmp/schema.sql The above script will generate a schema of all my SQL Server tables and will put it in the folder C:\tmp\schema.sql . You can open the schema.sql file and execute this file directly in your NuoDB instance. You can follow the link here to see how you can execute the SQL script in NuoDB. Please note that if you have not yet created the schema in the NuoDB database, you should create it before executing this step. Step 2: Generate the Dump File of the Data Once you have recreated your schema in NuoDB from SQL Server, the next step is very easy. Here we create a CSV format dump file, which will contain all the data from all the tables from the SQL Server database. The command to do so is very similar to the above command. Be aware that this step may take a bit of time based on your database size. nuodb-migrator dump –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.type=csv –output.path=/tmp/dump.cat Once the above command is successfully executed you can find your CSV file in the C:\tmp\ folder. However, you do not have to do anything manually. The third and final step will take care of completing the migration process. Migration Step 3: Load the Data into NuoDB After building schema and taking a dump of the data, the very next step is essential and crucial. It will take the CSV file and load it into the NuoDB database. nuodb-migrator load –target.url=jdbc:com.nuodb://localhost:48004/mytest –target.schema=dbo –target.username=test –target.password=test –input.path=/tmp/dump.cat Please note that in the above script we are now targeting the NuoDB database, which we have already created with the name of “MyTest”. If the database does not exist, create it manually before executing the above script. I have kept the username and password as “test”, but please make sure that you create a more secure password for your database for security reasons. Voila!  You’re Done That’s it. You are done. It took 3 setup and 3 migration steps to migrate your SQL Server database to NuoDB.  You can now start exploring the database and build excellent, scale-out applications. In this blog post, I have done my best to come up with simple and easy process, which you can follow to migrate your app from SQL Server to NuoDB. Download NuoDB I strongly encourage you to download NuoDB and go through my 3-step migration tutorial from SQL Server to NuoDB. Additionally here are two very important blog post from NuoDB CTO Seth Proctor. He has written excellent blog posts on the concept of the Administrative Domains. NuoDB has this concept of an Administrative Domain, which is a collection of hosts that can run one or multiple databases.  Each database has its own TEs and SMs, but all are managed within the Admin Console for that particular domain. http://www.nuodb.com/techblog/2013/03/11/getting-started-provisioning-a-domain/ http://www.nuodb.com/techblog/2013/03/14/getting-started-running-a-database/ Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: NuoDB

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  • In SqlAlchemy, how to ignore m2m relationship attributes when merge?

    - by ablmf
    There is a m2m relation in my models, User and Role. I want to merge a role, but i DO NOT want this merge has any effect on user and role relation-ship. Unfortunately, for some complicate reason, role.users if not empty. I tried to set role.users = None, but SA complains None is not a list. At this moment, I use sqlalchemy.orm.attributes.del_attribute, but I don't know if it's provided for this purpose.

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  • Fastest way to copy a set (100+) of related SQLAlchemy objects and change attribute on each one

    - by rebus
    I am developing an app that keeps track of items going in and out of factory. For example, lets say you have 3 kinds of plastic coming in, they are mixed in various ratios and then sent out as a new product. So to keep track of this I've created following database structure: This is very simplified overview of my SQLAlchemy models: IN <- RATIO <- OUT <- REPORT ITEMS -> REPORT IN are products coming in, RATIO is various information on measurements, and OUT is a final product. REPORT is basically a header model which has a lot of REPORT ITEMS attached to it, which in turn relate it to OUT products. This would all work perfectly, but IN and RATION values can change. These changes ultimately change the OUT product which would mean the REPORT values would change. So in order to change an attribute on IN object for example I should copy that object with that attribute changed. I would think this is basically a question about database normalization, because i didn't want to duplicate all the IN, RATIO and OUT information by writing it in REPORT ITEMS table for example, but I've came across this problem (well not really a problem but rather a feature I'd like for a user to have). When the attribute on IN object is changed I want related objects (RATIO and OUT) automatically copied and related to a new IN object. So I was thinking something like: Take an existing instance of model IN that needs to change (call it old_in) Create a new one out of it with some attributes changed (call it new_in) Collect all the RATIO objects that are related to old_in Copy each RATIO and relate them to a new_in Collect all the OUT objects that are related to old RATIO Copy each OUT and relate them to a new RATIO Few questions pop to mind when i look at this problem: Should i just duplicate the data, does all this copying even make sense? If it does, should i rather do it in plain SQL? If no what would be the best approach to do it with Python and SQLAlchemy? Any general answer would suffice really, at least a pointer in right direction. I really want to free then end user for hassle of having create new ratios and out products.

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  • Map only certain parts of the class to a database using SQLAlchemy?

    - by Az
    When mapping an object using SQLAlchemy, is there a way to only map certain elements of a class to a database, or does it have to be a 1:1 mapping? Example: class User(object): def __init__(self, name, username, password, year_of_birth): self.name = name self.username = username self.password = password self.year_of_birth = year_of_birth Say, for whatever reason, I only wish to map the name, username and password to the database and leave out the year_of_birth. Is that possible and will this create problems? Edit - 25/03/2010 Additionally, say I want to map username and year_of_birth to a separate database. Will this database and the one above still be connected (via username)?

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