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to_work #441
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@@ -24,7 +24,8 @@ | |
| "Nersc_Figure_Of_Merit", | ||
| ] | ||
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| _SUPPORTED_ENTRY_TYPES = ["LCF", "AWS", "Grid", "GCE"] | ||
| # _SUPPORTED_ENTRY_TYPES = ["LCF", "AWS", "Grid", "GCE"] | ||
| _SUPPORTED_ENTRY_TYPES = ["Grid"] | ||
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| METRICS = { | ||
| "NUMBER_OF_JOBS": Gauge("de_jobs_total", "Number of jobs seen by the Decision Engine"), | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This has been addressed by PR #440 |
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@@ -86,12 +87,9 @@ def transform(self, datablock): | |
| # Get factory global classad dataframe | ||
| factory_globals = datablock.get("factoryglobal_manifests") | ||
| factory_entries = datablock.get("Factory_Entries") | ||
| entries = pandas.DataFrame([]) | ||
| all_factory_entries = [ | ||
| factory_entries.xs(et) for et in _SUPPORTED_ENTRY_TYPES if et in factory_entries.index | ||
| ] | ||
| if all_factory_entries: | ||
| entries = pandas.DataFrame(pandas.concat(all_factory_entries, ignore_index=True, sort=True)) | ||
| entries = pandas.DataFrame( | ||
| pandas.concat([factory_entries.xs(et) for et in _SUPPORTED_ENTRY_TYPES], ignore_index=True, sort=True) | ||
| ) | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This has been addressed by PR #440 |
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| if entries.empty: | ||
| self.logger.info("There are no entries to request resources from") | ||
| return dict.fromkeys(["glideclientglobal_manifests", "glideclient_manifests"], pandas.DataFrame()) | ||
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@@ -25,9 +25,7 @@ def transform(self, datablock): | |
| """ | ||
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| self.logger.debug("in GridFigureOfMerit transform") | ||
| entries = pandas.DataFrame([]) | ||
| if "Grid" in self.Factory_Entries(datablock).index: | ||
| entries = self.Factory_Entries(datablock).xs("Grid") | ||
| entries = self.Factory_Entries(datablock).xs("Grid") | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This has been addressed by PR #440 |
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| if entries is None: | ||
| entries = pandas.DataFrame({ATTR_ENTRYNAME: []}) | ||
| foms = [] | ||
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@@ -29,8 +29,10 @@ def __init__(self, config): | |
| super().__init__(config) | ||
| self.condor_config = config.get("condor_config") | ||
| self.x509_user_proxy = config.get("x509_user_proxy") | ||
| self.max_retries = config.get("max_retries") | ||
| self.retry_interval = config.get("retry_interval") | ||
| # self.max_retries = config.get("max_retries") | ||
| self.max_retries = 10 | ||
| # self.retry_interval = config.get("retry_interval") | ||
| self.retry_interval = 1 | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. These changes are better addressed with changes in the configurations. |
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| self.update_ad_command = DEFAULT_UPDATE_AD_COMMAND | ||
| self.invalidate_ad_command = DEFAULT_INVALIDATE_AD_COMMAND | ||
| self.classad_type = "generic" | ||
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Checking with @mambelli, this change would require a full token setup, while the current one works with an hybrid X509 cert/token setup. We could end up to have two versions of DE depending on the specific setup.