Hi Francesc!
This big question is still open to me. We were playing around with
compression methods, chunk sizes and so on. But basicaly this was a
"production system". That's why I am working hard on that issue to avoid
this failure in future. (This was with python2.4.3 and pytables-1.3.2)
By the way, using python2.4.4 and pytables-1.3.3 I found a warning, that
was new to me:
/home/achim/local/lib/python2.4/site-packages/tables/Table.py:1971:
PerformanceWarning: table ``/data_pool/dict_Echo_Height__pos_`` is being
preempted from alive nodes without its buffers being flushed. This may
lead to very ineficient use of resources and even to fatal errors in
certain situations. Please, do a call to the .flush() method on this
table before start using other nodes.
Caller was write_hdf5:130 in file
/home/achim/damaris/frontends/reddamaris/DataPool.py.
PerformanceWarning)
I do not understand this:
What means "preempted from alive nodes"?
Does "this table" refer to dict_Echo_Height__pos_ or to the owners of
"alive nodes"
The node works with a table of 10 or 20 rows only.
h5_table_format= {
"x" : tables.Float64Col(),
"y_mean" : tables.Float64Col(),
"y_sigma" : tables.Float64Col(),
"n" : tables.Int64Col()
}
mr_table=hdffile.createTable(where=where,name=name,
description=h5_table_format,
title=title,
expectedrows=len(self))
mr_table.attrs.damaris_type="MeasurementResult"
self.lock.acquire()
try:
mr_table.attrs.quantity_name=self.quantity_name
row=mr_table.row
for x in self.get_xdata():
y=UserDict.UserDict.__getitem__(self,x)
row["x"]=x
if type(y) is types.FloatType:
row["y_mean"]=y
row["y_sigma"]=0.0
row["n"]=1
else:
row["y_mean"]=y.mean()
row["y_sigma"]=y.mean_sigma()
row["n"]=y.n
row.append()
finally:
#mr_table.flush()
self.lock.release()
This is the code. Till now I thought, there is no necessity for a
flush... ReReading the manual I fear, I did make a misstake. I added the
comment line and the warning vanished (of course removing the #).
Is it possible that both errors were related?
Yours, Achim
Francesc Altet wrote:
> Mmm... the question should rather be how you have been able to create a
> PyTables file with a leaf without a FLAVOR attribute. If you can
> reproduce the way, please, tell me (I'm very much intrigued).
>
> OTOH, in PyTables 2.0 the default for 'FLAVOR' will be 'numpy', of
> course. But until 2.0 arrives, a 'numarray' value is probably a more
> sensible default.
>
> Cheers,
>
>
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