PromHouse is a long-term remote storage with built-in clustering and downsampling for 2.x on top of
ClickHouse. Or, rather, it will be someday.
Feel free to like, share, retweet, star and watch it, but do not use it in production yet.
CREATE TABLE time_series (
date Date,
fingerprint UInt64,
labels String
)
ENGINE = ReplacingMergeTree
PARTITION BY date
ORDER BY fingerprint;
CREATE TABLE samples (
fingerprint UInt64,
timestamp_ms Int64,
value Float64
)
ENGINE = MergeTree
PARTITION BY toDate(timestamp_ms / 1000)
ORDER BY (fingerprint, timestamp_ms);
SELECT * FROM time_series WHERE fingerprint = 7975981685167825999;
┌───────date─┬─────────fingerprint─┬─labels─────────────────────────────────────────────────────────────────────────────────┐
│ 2017-12-31 │ 7975981685167825999 │ {"__name__":"up","instance":"promhouse_clickhouse_exporter_1:9116","job":"clickhouse"} │
└────────────┴─────────────────────┴────────────────────────────────────────────────────────────────────────────────────────┘
SELECT * FROM samples WHERE fingerprint = 7975981685167825999 LIMIT 3;
┌─────────fingerprint─┬──timestamp_ms─┬─value─┐
│ 7975981685167825999 │ 1514730532900 │ 0 │
│ 7975981685167825999 │ 1514730533901 │ 1 │
│ 7975981685167825999 │ 1514730534901 │ 1 │
└─────────────────────┴───────────────┴───────┘
Time series in Prometheus are identified by label name/value pairs, including __name__
label, which stores metric
name. Hash of those pairs is called a fingerprint. PromHouse uses the same hash algorithm as Prometheus to simplify data
migration. During the operation, all fingerprints and label name/value pairs a kept in memory for fast access. The new
time series are written to ClickHouse for persistence. They are also periodically read from it for discovering new time
series written by other ClickHouse instances. ReplacingMergeTree
ensures there are no duplicates if several ClickHouses
wrote the same time series at the same time.
PromHouse currently stores 24 bytes per sample: 8 bytes for UInt64 fingerprint, 8 bytes for Int64 timestamp, and 8 bytes for Float64 value. The actual compression rate is about 4.5:1, that's about 24/4.5 = 5.3 bytes per sample. Prometheus local storage compresses 16 bytes (timestamp and value) per sample to 1.37, that's 12:1.
- #167 update records should significantly simplify downsampling implementation.
- #838 Feature request: add ability to apply delta or delta-of-delta encoding to numeric columns before compression should improve compression rate.
The largest jobs and instances by time series count:
SELECT
job,
instance,
COUNT(*) AS value
FROM time_series
GROUP BY
visitParamExtractString(labels, 'job') AS job,
visitParamExtractString(labels, 'instance') AS instance
ORDER BY value DESC LIMIT 10
The largest metrics by time series count (cardinality):
SELECT
name,
COUNT(*) AS value
FROM time_series
GROUP BY
visitParamExtractString(labels, '__name__') AS name
ORDER BY value DESC LIMIT 10
The largest time series by samples count:
SELECT
labels,
value
FROM time_series
ANY INNER JOIN
(
SELECT
fingerprint,
COUNT(*) AS value
FROM samples
GROUP BY fingerprint
ORDER BY value DESC
LIMIT 10
) USING (fingerprint)