I am trying to read a 200 MB csv file using SQLalchemy. Each line has about 30 columns, of which, I use only 8 columns using the code below. However, the code runs really slow! Is there a way to improve this? I would like to use map/list comprehension or other techniques. As you an tell, I am a newbie. Thanks for your help.
for ddata in dread:
record = DailyData()
record.set_campaign_params(pdata) #Pdata is assigned in the previous step
record.set_daily_data(ddata) #data is sent to a class method where only 8 of 30 items in the list are used
session.add(record)
session.commit() #writing to the SQL database.
don't commit on every record. commit or just flush every 1000 or so:
for i, data in enumerate(csv_stuff):
rec = MyORMObject()
rec.set_stuff(data)
session.add(rec)
if i % 1000 == 0:
session.flush()
session.commit() # flushes everything remaining + commits
if that's still giving you problems then do some basic profiling, see my post at How can I profile a SQLAlchemy powered application?
Related
What I am trying to accomplish => Run 50 threads in parallel using a CSV file as the dataset.
Here's how the CSV looks like (Let's say there are 50 records):
Username,Password
user1,password1
user2,password2
...,...
user50, password50
In JMeter, when I run my test case, each thread will consume 1 record of the CSV file in parallel. By that I mean, Thread 1 takes the first record (user1,password1), Thread 2 takes the second record (user2,password2), until the last record (50 in this example). And all of that happens at the same time.
I am still new to JMeter and I would like to know if this is something that is "doable" through this tool. If it is possible, your help is greatly appreciated! :)
Given default CSV Data Set Config setup which looks like:
each thread (virtual user) will take next line of the CSV file on each loop (iteration)
when the last line of the CSV file will be reached it will start over from the beginning
With regards to your "at the same time" requirement - the load pattern is controlled by Thread Group settings (number of threads, loops, ramp-up period), depending on your setup you will have concurrency from 0 to 50 active users, you can observe it using i.e. Active Threads Over Time listener
If you want to send 50 requests at exactly the same moment - consider using Synchronizing Timer
This is possible using CSV Data Set Config element. It reads the data row by row and username and password can be assigned to each thread. You can use the values with following syntax
Username ${Username}
password ${Password}
Also please note that you do not have to define the variable names in the CSV Dataset Config Element as you have them in the first row of the CSV file.
I was stuck in a situation that I have initialised a namesapce with
default-ttl to 30 days. There was about 5 million data with that (30-day calculated) ttl-value. Actually, my requirement is that ttl should be zero(0), but It(ttl-30d) was kept with unaware or un-recognise.
So, Now I want to update prev(old) 5 million data with new ttl-value (Zero).
I've checked/tried "set-disable-eviction true", but it is not working, it is removing data according to (old)ttl-value.
How do I overcome out this? (and I want to retrieve the removed data, How can I?).
Someone help me.
First, eviction and expiration are two different mechanisms. You can disable evictions in various ways, such as the set-disable-eviction config parameter you've used. You cannot disable the cleanup of expired records. There's a good knowledge base FAQ What are Expiration, Eviction and Stop-Writes?. Unfortunately, the expired records that have been cleaned up are gone if their void time is in the past. If those records were merely evicted (i.e. removed before their void time due to crossing the namespace high-water mark for memory or disk) you can cold restart your node, and those records with a future TTL will come back. They won't return if either they were durably deleted or if their TTL is in the past (such records gets skipped).
As for resetting TTLs, the easiest way would be to do this through a record UDF that is applied to all the records in your namespace using a scan.
The UDF for your situation would be very simple:
ttl.lua
function to_zero_ttl(rec)
local rec_ttl = record.ttl(rec)
if rec_ttl > 0 then
record.set_ttl(rec, -1)
aerospike:update(rec)
end
end
In AQL:
$ aql
Aerospike Query Client
Version 3.12.0
C Client Version 4.1.4
Copyright 2012-2017 Aerospike. All rights reserved.
aql> register module './ttl.lua'
OK, 1 module added.
aql> execute ttl.to_zero_ttl() on test.foo
Using a Python script would be easier if you have more complex logic, with filters etc.
zero_ttl_operation = [operations.touch(-1)]
query = client.query(namespace, set_name)
query.add_ops(zero_ttl_operation)
policy = {}
job = query.execute_background(policy)
print(f'executing job {job}')
while True:
response = client.job_info(job, aerospike.JOB_SCAN, policy={'timeout': 60000})
print(f'job status: {response}')
if response['status'] != aerospike.JOB_STATUS_INPROGRESS:
break
time.sleep(0.5)
Aerospike v6 and Python SDK v7.
I describe the outcome of a strategy by numerous rows. Each row contains a symbol (describing an asset), a timestamp (think of a backtest) and a price + weight.
Before a strategy runs I delete all previous results from this particular strategy (I have many strategies). I then loop over all symbols and all times.
# delete all previous data written by this strategy
StrategyRow.objects.filter(strategy=strategy).delete()
for symbol in symbols.keys():
s = symbols[symbol]
for t in portfolio.prices.index:
p = prices[symbol][t]
w = weights[symbol][t]
row = StrategyRow.objects.create(strategy=strategy, symbol=s, time=t)
if not math.isnan(p):
row.price = p
if not math.isnan(w):
row.weight = w
row.save()
This works but is very, very slow. Is there a chance to achive the same with write_frame from pandas? Or maybe using faster raw sql?
I don't think the first thing you should try is the raw SQL route (more on that in a bit)
But I think it's because of calling row.save() on many objects, that operation is known to be slow.
I'd look into StrategyRow.objects.bulk_create() first, https://docs.djangoproject.com/en/1.7/ref/models/querysets/#django.db.models.query.QuerySet.bulk_create
The difference is you pass it a list of your StrategyRow model, instead of calling .save() on individual instances. It's pretty straightforward, bundle up a few rows then create them in batches, maybe try 10, 20, a 100 etc at a time, your database configs can also help find the optimum batch size. (e.g. http://dev.mysql.com/doc/refman/5.5/en/server-system-variables.html#sysvar_max_allowed_packet)
Back to your idea of raw SQL, that would make a difference, if e.g. the Python code that creates the StrategyRow instances is slow (e.g. StrategyRow.objects.create()), but still I believe the key is to batch insert them instead of running N queries
We have a hybrid web application integrating a MySql db with Plone (last upgrade was to Plone 4.0), using collective.tin, collective.lead and SqlAlchemy.
Ok, I know that collective.tin never was released and collective.lead has been superseded; however all things work (almost) perfectly since a few years.
Recently we experienced a very strange behaviour and are looking for help in order to understand it.
Among others, we have 2 Plone content types, say A and B, defined by subclassing collective.tin, and the corresponding innodb MySql tables; rows of B have a foreign key towards A.
In the time span of 15-20 minutes, 2 different users created 3 A objects and some 10-20 B objects that weren't committed to MySql but were indexed by Plone; queries I executed with a MySql client from the linux shell weren't able to find those A rows (didn't look for B rows); however, queries executed through the web application (the aforementioned components stack) by those 2 users, and also by other users, occasionally were still finding and correctly visualizing some of those 3 A objects.
Only after I restarted the Zope instance, it was possible to resume normal activity from the Plone web interface; 3 A rows and many B rows were still missing from the MySql db, but the autoincrement counter showed the expected increment; I had to remove 3 invalid brains for A objects from the Plone index (didn't worry for B objects).
Any suggestion on possible causes and on how to investigate the problem?
We had the exact same problem with sqlalchemy 0.4; the session would get out of sync with the actual database contents. The problem was somewhat masked in our case because users were sent to specific backends in the cluster through session affinity. If the affinity was lost suddenly messages had disappeared. The exact details are a little hazy, because I cannot locate the correct (ancient) revision history of the fix I put in place.
From what I can glean from context is that the session identity map prevents the session from requiring the database for objects it retrieved before. It thus won't see changes made to these objects in different sessions.
The fix is to call .expire_all() on the session after each and every commit or rollback; SQLAlchemy 0.5 and up does this automatically (autoexpire=True on the session, now called expire_on_commit I believe), but for 0.4 you'll need to register a SessionExtension to do this for you.
Lucky for you, we also use collective.lead for this project, so my fix is your fix:
# The identity map should be flushed on commit.
# SQLAlchemy 0.5 does this properly, but in 0.4 we need to do this via
# a SesssionExtension.
from sqlalchemy import __version__
if __version__[:3] == '0.4':
from sqlalchemy.orm.session import SessionExtension
class ExpireAllSessionExtension(SessionExtension):
def after_commit(self, session):
"""Expire the identity-map on commit"""
session.expire_all()
def after_rollback(self, session):
"""Expire the identity-map on rollback"""
session.expire_all()
def installExtension():
# Patch collective.lead.database to let us install the extension
# on the session created there.
from collective.lead.database import Database
old_session = Database.session.fget
def session(self):
session = old_session(self)
if session.extension is None:
session.extension = ExpireAllSessionExtension()
return session
Database.session = property(session)
else:
def installExtension():
pass
When defining the mapper, you install this extension with:
from .sessionexpiration import installExtension
# Ensure that sessions get properly expired on commit and rollback.
installExtension()
I am currently trying to move my DB tables over to InnoDB from MyISAM. I am having timing issues with requests and cron jobs that are running on the server that is leading to some errors. I am quite sure that transaction support will help me with the problem. I am therefore transitioning to InnoDB.
I have a suite of tests which make calls to our webservices REST API and receive XML responses. The test suite is fairly thorough, and it's written in Python and uses SQLAlchemy to query information from the database. When I change the tables in the system from MyISAM to InnoDB however, the tests start failing. However, the tests aren't failing because the system isn't working, they are failing because the ORM is not correctly querying the rows from the database I am testing on. when I step through the code I see the correct results, but the ORM is not returning the correct results at all.
Basic flow is:
class UnitTest(unittest.TestCase):
def setUp(self):
# Create a test object in DB that gets affected by the web server
testObject = Obj(foo='one')
self.testId = testObject.id
session.add(testObject)
session.commit()
def tearDown(self):
# Clean up after the test
testObject = session.query(Obj).get(self.testId)
session.delete(testObject)
session.commit()
def test_web_server(self):
# Ensure the initial state of the object.
objects = session.query(Obj).get(self.testId)
assert objects.foo == 'one'
# This will make a simple HTTP get call on an url that will modify the DB
response = server.request.increment_foo(self.testId)
# This one fails, the object still has a foo of 'one'
# When I stop here in a debugger though, and look at the database,
# The row in question actually has the correct value in the database.
# ????
objects = session.query(Obj).get(self.testId)
assert objects.foo == 'two'
Using MyISAM tables to store the object and this test will pass. However, when I change to InnoDB tables, this test will not pass. What is more interesting is that when I step through the code in the debugger, I can see that the datbase has what I expect, so it's not a problem in the web server code. I have tried nearly every combination of expire_all, autoflush, autocommit, etc. etc, and still can't get this test to pass.
I can provide more info if necessary.
Thanks,
Conrad
The problem is that you put the line self.testId = testObject.id before new object is added to session, flushed, and SQLAlchemy assigned ID to it. Thus self.testId is always None. Move this line below session.commit().