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docs/Single-server-VictoriaMetrics.md: imrpove docs about metrics deletion
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@ -602,7 +602,7 @@ Steps for restoring from a snapshot:
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Send a request to `http://<victoriametrics-addr>:8428/api/v1/admin/tsdb/delete_series?match[]=<timeseries_selector_for_delete>`,
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Send a request to `http://<victoriametrics-addr>:8428/api/v1/admin/tsdb/delete_series?match[]=<timeseries_selector_for_delete>`,
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where `<timeseries_selector_for_delete>` may contain any [time series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors)
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where `<timeseries_selector_for_delete>` may contain any [time series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors)
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for metrics to delete. After that all the time series matching the given selector are deleted. Storage space for
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for metrics to delete. After that all the time series matching the given selector are deleted. Storage space for
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the deleted time series isn't freed instantly - it is freed during subsequent merges of data files.
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the deleted time series isn't freed instantly - it is freed during subsequent [background merges of data files](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282).
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It is recommended verifying which metrics will be deleted with the call to `http://<victoria-metrics-addr>:8428/api/v1/series?match[]=<timeseries_selector_for_delete>`
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It is recommended verifying which metrics will be deleted with the call to `http://<victoria-metrics-addr>:8428/api/v1/series?match[]=<timeseries_selector_for_delete>`
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before actually deleting the metrics.
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before actually deleting the metrics.
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@ -617,9 +617,10 @@ The delete API is intended mainly for the following cases:
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It isn't recommended using delete API for the following cases, since it brings non-zero overhead:
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It isn't recommended using delete API for the following cases, since it brings non-zero overhead:
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* Regular cleanups for unneded data. Just prevent writing unneeded data into VictoriaMetrics.
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* Regular cleanups for unneded data. Just prevent writing unneeded data into VictoriaMetrics.
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This can be done with relabeling in [vmagent](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmagent/README.md).
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See [this article](https://www.robustperception.io/relabelling-can-discard-targets-timeseries-and-alerts) for details.
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See [this article](https://www.robustperception.io/relabelling-can-discard-targets-timeseries-and-alerts) for details.
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* Reducing disk space usage by deleting unneded time series. This doesn't work as expected, since the deleted
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* Reducing disk space usage by deleting unneded time series. This doesn't work as expected, since the deleted
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time series occupy disk space until the next merge operation, which can never occur.
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time series occupy disk space until the next merge operation, which can never occur when deleting too old data.
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It is better using `-retentionPeriod` command-line flag for efficient pruning of old data.
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It is better using `-retentionPeriod` command-line flag for efficient pruning of old data.
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@ -602,7 +602,7 @@ Steps for restoring from a snapshot:
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Send a request to `http://<victoriametrics-addr>:8428/api/v1/admin/tsdb/delete_series?match[]=<timeseries_selector_for_delete>`,
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Send a request to `http://<victoriametrics-addr>:8428/api/v1/admin/tsdb/delete_series?match[]=<timeseries_selector_for_delete>`,
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where `<timeseries_selector_for_delete>` may contain any [time series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors)
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where `<timeseries_selector_for_delete>` may contain any [time series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors)
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for metrics to delete. After that all the time series matching the given selector are deleted. Storage space for
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for metrics to delete. After that all the time series matching the given selector are deleted. Storage space for
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the deleted time series isn't freed instantly - it is freed during subsequent merges of data files.
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the deleted time series isn't freed instantly - it is freed during subsequent [background merges of data files](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282).
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It is recommended verifying which metrics will be deleted with the call to `http://<victoria-metrics-addr>:8428/api/v1/series?match[]=<timeseries_selector_for_delete>`
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It is recommended verifying which metrics will be deleted with the call to `http://<victoria-metrics-addr>:8428/api/v1/series?match[]=<timeseries_selector_for_delete>`
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before actually deleting the metrics.
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before actually deleting the metrics.
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@ -617,9 +617,10 @@ The delete API is intended mainly for the following cases:
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It isn't recommended using delete API for the following cases, since it brings non-zero overhead:
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It isn't recommended using delete API for the following cases, since it brings non-zero overhead:
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* Regular cleanups for unneded data. Just prevent writing unneeded data into VictoriaMetrics.
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* Regular cleanups for unneded data. Just prevent writing unneeded data into VictoriaMetrics.
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This can be done with relabeling in [vmagent](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmagent/README.md).
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See [this article](https://www.robustperception.io/relabelling-can-discard-targets-timeseries-and-alerts) for details.
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See [this article](https://www.robustperception.io/relabelling-can-discard-targets-timeseries-and-alerts) for details.
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* Reducing disk space usage by deleting unneded time series. This doesn't work as expected, since the deleted
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* Reducing disk space usage by deleting unneded time series. This doesn't work as expected, since the deleted
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time series occupy disk space until the next merge operation, which can never occur.
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time series occupy disk space until the next merge operation, which can never occur when deleting too old data.
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It is better using `-retentionPeriod` command-line flag for efficient pruning of old data.
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It is better using `-retentionPeriod` command-line flag for efficient pruning of old data.
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