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202692f1ef
Tests are updated to no longer use continuous aggregate options that will be removed, such as `refresh_lag`, `max_interval_per_job` and `ignore_invalidation_older_than`. `REFRESH MATERIALIZED VIEW` has also been replaced with `CALL refresh_continuous_aggregate()` using ranges that try to replicate the previous refresh behavior. The materializer test (`continuous_aggregate_materialize`) has been removed, since this tested the "old" materializer code, which is no longer used without `REFRESH MATERIALIZED VIEW`. The new API using `refresh_continuous_aggregate` already allows manual materialization and there are two previously added tests (`continuous_aggs_refresh` and `continuous_aggs_invalidate`) that cover the new refresh path in similar ways. When updated to use the new refresh API, some of the concurrency tests, like `continuous_aggs_insert` and `continuous_aggs_multi`, have slightly different concurrency behavior. This is explained by different and sometimes more conservative locking. For instance, the first transaction of a refresh serializes around an exclusive lock on the invalidation threshold table, even if no new threshold is written. The previous code, only took the heavier lock once, and if, a new threshold was written. This new, and stricter locking, means that insert processes that read the invalidation threshold will block for a short time when there are concurrent refreshes. However, since this blocking only occurs during the first transaction of the refresh (which is quite short), it probably doesn't matter too much in practice. The relaxing of locks to improve concurrency and performance can be implemented in the future.
38 lines
1.5 KiB
SQL
38 lines
1.5 KiB
SQL
-- This file and its contents are licensed under the Timescale License.
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-- Please see the included NOTICE for copyright information and
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-- LICENSE-TIMESCALE for a copy of the license.
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CREATE TABLE jit_test(time timestamp NOT NULL, device int, temp float);
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SELECT create_hypertable('jit_test', 'time');
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ALTER TABLE jit_test DROP COLUMN device;
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CREATE TABLE jit_test_interval(id int NOT NULL, temp float);
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SELECT create_hypertable('jit_test_interval', 'id', chunk_time_interval => 10);
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CREATE TABLE jit_test_contagg (
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observation_time TIMESTAMPTZ NOT NULL,
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device_id TEXT NOT NULL,
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metric DOUBLE PRECISION NOT NULL,
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PRIMARY KEY(observation_time, device_id)
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);
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SELECT table_name FROM create_hypertable('jit_test_contagg', 'observation_time');
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CREATE MATERIALIZED VIEW jit_device_summary
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WITH (timescaledb.continuous)
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AS
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SELECT
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time_bucket('1 hour', observation_time) as bucket,
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device_id,
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avg(metric) as metric_avg,
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max(metric)-min(metric) as metric_spread
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FROM
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jit_test_contagg
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GROUP BY bucket, device_id WITH NO DATA;
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INSERT INTO jit_test_contagg
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SELECT ts, 'device_1', (EXTRACT(EPOCH FROM ts)) from generate_series('2018-12-01 00:00'::timestamp, '2018-12-31 00:00'::timestamp, '30 minutes') ts;
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INSERT INTO jit_test_contagg
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SELECT ts, 'device_2', (EXTRACT(EPOCH FROM ts)) from generate_series('2018-12-01 00:00'::timestamp, '2018-12-31 00:00'::timestamp, '30 minutes') ts;
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CALL refresh_continuous_aggregate('jit_device_summary', NULL, NULL);
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