Related Github Repos and tickets

https://github.com/aria-jpl/topsstack
Tickets:
- https://jira.jpl.nasa.gov/browse/ARIA-42
- ARIA-47 - Getting issue details... STATUS
- https://jira.jpl.nasa.gov/browse/ARIA-8

Job Runtime

Depends on how many SLCs are being processed
1+ hours for 8 SLCs

GNU Parallel

c5d.9xlarge

(36 vCPU, 72 GiB)

c5.24xlarge

(96 vCPU, 192 GiB)

1 year (~30 SLCS, 4 bursts)

7 hrs, 24 mins, 46 secs

4 hrs, 38 mins, 33 secs

2 year (~60 SLCS, 4 bursts)

13 hrs, 37 mins, 39 secs

8 hrs, 16 min, 46 secs

Multiprocessing

	c5d.9xlarge (36 vCPU, 72 GiB)	c5.24xlarge (96 vCPU, 192 GiB)
1 year (~30 SLCS, 4 bursts)	6 hrs, 43 mins, 27 secs	4 hrs, 19 mins, 30 secs
2 year (~60 SLCS, 4 bursts)	12 hrs, 58 mins, 32 secs	8 hrs, 30 mins, 43 secs
3 year (~90 SLCS, 4 bursts)	18 hrs, 14 mins, 44 secs	10 hrs, 56 mins, 5 secs

Objective

Creating a stack of SLCs

Only within the same track (over a time period)

Prerequisite to STAMPS processing

How to set up the inputs

Facets to get SLC inputs
- region (ex. Hawaii) (optional)
- track_number or trackNumber (depends)
- datatype: SLC

If SLCs track number do not match, then it would throw this error in the job:

raise  Exception('Could not determine a suitable burst offset')

There must only be one track in your SLC inputs

correct facet SLC inputs incorrect facet SLC inputs

Job Inputs:

Bbox (*required)
- min_lat max_lat min_lon max_lon

CI Integration (Jenkins)

ops-bcluster_container-builder_aria-jpl_topsstack_master
Link: http://b-ci.grfn.hysds.io:8080/job/ops-bcluster_container-builder_aria-jpl_topsstack_master/
- WARNING: If rebuilding on the same branch (master), make sure to remove docker image so that it reloads when restarting the job: docker rmi <topsStack docker image id>

HySDS-io and Jobspec-io

hysds-io.json.topsstack

{
  "label": "topsStack Processor",
  "submission_type": "individual",
  "allowed_accounts": [ "ops" ],
  "action-type":  "both",
  "params": [
    {
      "name": "min_lat",
      "from": "submitter",
      "type": "number",
      "optional": false
    },
    {
      "name": "max_lat",
      "from": "submitter",
      "type": "number",
      "optional": false
    },
    {
      "name": "min_lon",
      "from": "submitter",
      "type": "number",
      "optional": false
    },
    {
      "name": "max_lon",
      "from": "submitter",
      "type": "number",
      "optional": false
    },
    {
      "name":"localize_products",
      "from":"dataset_jpath:",
      "type":"text",
      "lambda" : "lambda met: get_partial_products(met['_id'],get_best_url(met['_source']['urls']),[met['_id']+'.zip'])"
    }
  ]
}

job-spec.json.topsstack

{
  "recommended_queues": ["jjacob_stack"],
  "command": "/home/ops/verdi/ops/topsstack/run_stack.sh",
  "imported_worker_files": {
    "/home/ops/.netrc": "/home/ops/.netrc",
    "/home/ops/.aws": "/home/ops/.aws"
  },
  "soft_time_limit": 10800,
  "time_limit": 18000,
  "disk_usage": "100GB",
  "params": [
    {
      "name": "min_lat",
      "destination": "context"
    },
    {
      "name": "max_lat",
      "destination": "context"
    },
    {
      "name": "min_lon",
      "destination": "context"
    },
    {
      "name": "max_lon",
      "destination": "context"
    },
    {
      "name":"localize_products",
      "destination": "localize"
    } 
  ]
}

Job Outputs

Main file that gets executed is run_stack.sh

Copies all SLCs .zip files to zip/ sub-directory
runs get_bbox.py and exports 8 coordinates as inputs for the science code
- read MINLAT MAXLAT MINLON MAXLON MINLAT_LO MAXLAT_HI MINLON_LO MAXLON_HI <<< $TOKENS
Runs 10 steps to complete the stack processor
- run.py -i ./run_files/run_1_unpack_slc_topo_master -p 8
- run.py -i ./run_files/run_2_average_baseline -p 8
- run.py -i ./run_files/run_3_extract_burst_overlaps -p 8
- run.py -i ./run_files/run_4_overlap_geo2rdr_resample -p 8
- run.py -i ./run_files/run_5_pairs_misreg -p 8
- run.py -i ./run_files/run_6_timeseries_misreg -p 8
- run.py -i ./run_files/run_7_geo2rdr_resample -p 8
- run.py -i ./run_files/run_8_extract_stack_valid_region -p 8
- run.py -i ./run_files/run_9_merge -p 8
- run.py -i ./run_files/run_10_grid_baseline -p 8

Output directory structure

Output structure of merged/

merged/
    baselines/
        20190506/
        20190518/
        20190530/
            20190530
            20190530.full.vrt
            20190530.vrt
            20190530.xml
    geom_master/
	    *.rdr.aux.xml
        *.rdr.full
        *.rdr.full.aux.xml
        *.rdr.full.vrt
        *.rdr.full.xml
    SLC/
        20190506/
        20190518/
        20190530/
            20190530.slc.full
            20190530.slc.full.aux.xml
            20190530.slc.full.vrt
            20190530.slc.full.xml
            20190530.slc.hdr

Datasets.json entry

file located in .sds/files/datasets.json

{
  "ipath": "ariamh::data/STACK",
  "match_pattern": "/(?P<id>coregistered_slcs-(?P<year>\\d{4})(?P<month>\\d{2})(?P<day>\\d{2})(?P<time>\\d{6}).+)$",
  "alt_match_pattern": null,
  "extractor": null,
  "level": "NA",
  "type": "stack",
  "publish": {
    "s3-profile-name": "default",
    "location": "s3://s3-us-west-2.amazonaws.com:80/##BUCKET##/datasets/{type}/{version}/{year}/{month}/{day}/{id}",
    "urls": [
      "http://##WEBDAV_URL##/datasets/{type}/{version}/{year}/{month}/{day}/{id}",
      "s3://##S3_URL##:80/##BUCKET##/datasets/{type}/{version}/{year}/{month}/{day}/{id}"
    ]
  },
  "browse": {
    "location": "davs://##WEBDAV_USER##@##WEBDAV USER##/browse/{type}/{version}/{year}/{month}/{day}/{id}",
    "urls": [
      "https://##WEBDAV##/browse/{type}/{version}/{year}/{month}/{day}/{id}"
    ],
  }
}

Running on ASG (Auto Scaling Group)

Currently using c5d.9xlarge
- Not enough CPU
- Takes 11.5 Hrs to run 30 scenes
May need to upgrade to c5d.18xlarge or i-instances

STILL TODO:

Integrate Sang-Ho/Jungkyo GNU parallel

TopsStack Processor (PGE)