# DMTN-053: Observations on I/O activity induced by ingestImages.py and processCcd.py

• Fabio Hernandez,
• Dominique Boutigny and
• Loic Tortay

Latest Revision: 2017-08-08

# 1   Introduction¶

While processing processing HSC data using the LSST stack in IN2P3 computing center (CC-IN2P3) batch farm, a rather low CPU efficiency (i.e. the ratio CPU time/wall time) was observed.

At CC-IN2P3, both the raw HSC images and the resulting reduced images are stored in a GPFS cluster. It was hypothesized that the observed batch jobs’ undesired behavior could be linked to some GPFS client thrashing, so we decided to investigate.

This note summarizes what we observed in the early analysis pass. It was first published as a LSST community post, where you can find some feedback provided by experts on the LSST software framework.

# 2   Testing environment¶

Our deliberately simple test is composed of two steps:

1. ingest a single raw image (one CCD) using ingestImage.py
2. use processCcd.py for processing a single CCD image

For our tests we use the LSST weekly version w_2017_29 (Python 3) on a compute node running CentOS 7. The compute node runs the GPFS client and is connected to the GPFS cluster by a 10 Gbps network link. The GPFS client is configured to use 8 GB of RAM for caching data.

# 3   Image ingestion¶

The HSC raw images are found in the raw directory of our testing environment. The command we use for building the image registry is:


span.prompt1:before {
content: "$"; } ingestImages.py data ./raw/HSCA01151351.fits --mode link  As a result of this, among other things, a file registry.sqlite3 is created in the data directory. In our case, both the data directory and the raw directory reside on GPFS. $ tree data
data
├── _mapper
├── registry.sqlite3
└── SSP_UDEEP_SXDS
└── 2014-11-18
└── 01052
└── HSC-R
└── HSC-0011512-105.fits -> /sps/lsst/dev/fabio/hscIO/ingest/raw/HSCA01151351.fits

4 directories, 3 files


In the process of populating registry.sqlite3, the sqlite3 library creates some temporary files (with extensions -journal or -wal) in the same directory as the final destination file, i.e. data. It also repeatedly acquires and releases locks on those temporary files. When the population of the registry file is finished, the temporary file is renamed to its final name registry.sqlite3.

Locking files or portion of files in a shared file system is a potentially costly operation since a synchronization of all the nodes using the file system is required to honor POSIX semantics. According to the SQLite documentation, there is a way to instruct the library where to create temporary files. It didn’t work in our tests: setting the values of one of the environmental variables SQLITE_TMPDIR, TMPDIR or TMP had no effect when using a test program linking against the sqlite3 shared library shipped with the stack.

It would be worth considering the command line tasks of the stack to create any temporary file in the local storage of the compute node (either local scratch disk or even RAM disk) and to copy those files back to their final destination (i.e. the data directory in GPFS in this particular case) when they are no longer needed. The command line tasks could look for the value of the POSIX TMPDIR variable for the location to store those temporary files. Processing sites would then set the TMPDIR variable to the appropriate location for each job to use for scratch storage.

# 4   Process CCD¶

The command for this test is:

processCcd.py input --output output --id visit=38080 ccd=23


To our knowledge, there is nothing special with this particular visit and this particular CCD. The size of the input image file of CCD 23 is 17 MB and its format is FITS.

At the end of the process several files are created under the output directory:

\$ tree output
output
├── 01318
│   └── HSC-I
│       ├── corr
│       │   ├── BKGD-0038080-023.fits
│       │   └── CORR-0038080-023.fits
│       ├── output
│       │   ├── ICSRC-0038080-023.fits
│       │   ├── SRC-0038080-023.fits
│       │   ├── SRCMATCH-0038080-023.fits
│       │   └── SRCMATCHFULL-0038080-023.fits
│       │   └── 0038080-023.boost
│       └── thumbs
│           ├── flattened-0038080-023.png
│           └── oss-0038080-023.png
├── config
│   ├── packages.pickle
│   └── processCcd.py
├── repositoryCfg.yaml
└── schema
├── icSrc.fits
└── src.fits

8 directories, 14 files


As in the previous step, we collected the I/O activity using the strace(1) utility and then analysed its output. In the table below you can find the summary of the activity related to some of the files generated in this step. The Read column is the amount of data read using the read(2) system call when populating the file and analogously, the Write column is the amount of data written via the write(2) system call.

Table 1 Summary of the I/O activity on selected files generated by the processCcd.py command above.
File Name File Size (MB) Read (MB) Write (MB)
output/01318/HSC-I/output/ICSRC-0038080-023.fits 1 265 3
output/01318/HSC-I/output/SRC-0038080-023.fits 12 2299 24
output/01318/HSC-I/output/SRCMATCH-0038080-023.fits 0 0 0
output/01318/HSC-I/output/SRCMATCHFULL-0038080-023.fits 0 47 1
output/01318/HSC-I/corr/BKGD-0038080-023.fits 0 1 0
output/01318/HSC-I/corr/CORR-0038080-023.fits 98 13 98
output/schema/icSrc.fits 0 15 0
output/schema/src.fits 0 0 0

Notice that for instance, for generating the file SRC-0038080-023.fits which has a final size of 12 MB, the process read 2299 MB, that is, 191 times the file final size. In the same way, writing 1 MB to the file ICSRC-0038080-023.fits required reading 265 MB from it, or 265 times its size.

This looks really suspicious and is likely unintended. If we look in detail what is happening at the file system level, we can see a pattern:

• write some FITS key-value pairs in the first HDU header (11520 bytes)
• set the file position to 0
• read all the contents of the file written so far
• write some data to the file (typically a FITS HDU, that is, 2880 bytes)
• set the file position to 0
• read all the contents of the file written so far
• write some data to the file (typically a FITS HDU, that is, 2880 bytes)
• set the file position to 0
• read all the contents of the file written so far
• and so on...

It is not clear why it is necessary to re-read the whole file before each write operation. But if this is the intended behavior, this may be done in a scratch area local to the compute node and copy the result to the final destination when appropriate. Given the sizes of the generated files, the amount of storage local to the compute node is unlikely to be the limiting factor.

The details of all the I/O activity on those 2 files, as reported by strace(1), are available here.

# 5   Conclusion¶

The work on understading the I/O activity induced by the LSST command line tasks is just starting. We consider this a very important ingredient for designing the storage infrastructure that best suits the needs of bulk LSST data processing. Initial results using the LSST software with precursor datasets show that there are several aspects of the behavior of this software that needs to be understood and fed back to the developers.