d0b02dc0d0
Currently when a partition is deleted from the base table, we generate a row tombstone update for each one of the view rows in the partition. When the partition key in the view is the same as the base, maybe in a different order, this can be done more efficiently - The whole corresponding view partition can be deleted with one partition tombstone update. With this commit, when generating view updates, if the update mutation has a partition tombstone then for the views which have the same partition key we will generate a partition tombstone update, and skip the individual row tombstone updates. Fixes scylladb/scylladb#8199
1192 lines
73 KiB
Python
1192 lines
73 KiB
Python
# Copyright 2021-present ScyllaDB
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#
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# SPDX-License-Identifier: AGPL-3.0-or-later
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# Tests for materialized views
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import time
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import pytest
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from util import new_test_table, unique_name, new_materialized_view, ScyllaMetrics
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from cassandra.protocol import InvalidRequest, SyntaxException
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import nodetool
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# Test that building a view with a large value succeeds. Regression test
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# for a bug where values larger than 10MB were rejected during building (#9047)
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def test_build_view_with_large_row(cql, test_keyspace):
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schema = 'p int, c int, v text, primary key (p,c)'
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mv = unique_name()
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with new_test_table(cql, test_keyspace, schema) as table:
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big = 'x'*11*1024*1024
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cql.execute(f"INSERT INTO {table}(p,c,v) VALUES (1,1,'{big}')")
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cql.execute(f"CREATE MATERIALIZED VIEW {test_keyspace}.{mv} AS SELECT * FROM {table} WHERE p IS NOT NULL AND c IS NOT NULL PRIMARY KEY (c,p)")
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try:
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retrieved_row = False
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for _ in range(50):
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res = [row for row in cql.execute(f"SELECT * FROM {test_keyspace}.{mv}")]
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if len(res) == 1 and res[0].v == big:
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retrieved_row = True
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break
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else:
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time.sleep(0.1)
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assert retrieved_row
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finally:
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cql.execute(f"DROP MATERIALIZED VIEW {test_keyspace}.{mv}")
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# Test that updating a view with a large value succeeds. Regression test
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# for a bug where values larger than 10MB were rejected during building (#9047)
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def test_update_view_with_large_row(cql, test_keyspace):
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schema = 'p int, c int, v text, primary key (p,c)'
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mv = unique_name()
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with new_test_table(cql, test_keyspace, schema) as table:
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cql.execute(f"CREATE MATERIALIZED VIEW {test_keyspace}.{mv} AS SELECT * FROM {table} WHERE p IS NOT NULL AND c IS NOT NULL PRIMARY KEY (c,p)")
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try:
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big = 'x'*11*1024*1024
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cql.execute(f"INSERT INTO {table}(p,c,v) VALUES (1,1,'{big}')")
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res = [row for row in cql.execute(f"SELECT * FROM {test_keyspace}.{mv}")]
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assert len(res) == 1 and res[0].v == big
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finally:
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cql.execute(f"DROP MATERIALIZED VIEW {test_keyspace}.{mv}")
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# Test that a `CREATE MATERIALIZED VIEW` request, that contains bind markers in
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# its SELECT statement, fails gracefully with `InvalidRequest` exception and
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# doesn't lead to a database crash.
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def test_mv_select_stmt_bound_values(cql, test_keyspace):
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schema = 'p int PRIMARY KEY'
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mv = unique_name()
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with new_test_table(cql, test_keyspace, schema) as table:
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try:
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with pytest.raises(InvalidRequest, match="CREATE MATERIALIZED VIEW"):
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cql.execute(f"CREATE MATERIALIZED VIEW {test_keyspace}.{mv} AS SELECT * FROM {table} WHERE p = ? PRIMARY KEY (p)")
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finally:
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cql.execute(f"DROP MATERIALIZED VIEW IF EXISTS {test_keyspace}.{mv}")
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# In test_null.py::test_empty_string_key() we noticed that an empty string
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# is not allowed as a partition key. However, an empty string is a valid
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# value for a string column, so if we have a materialized view with this
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# string column becoming the view's partition key - the empty string may end
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# up being the view row's partition key. This case should be supported,
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# because the "IS NOT NULL" clause in the view's declaration does not
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# eliminate this row (an empty string is *not* considered NULL).
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# Reproduces issue #9375.
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def test_mv_empty_string_partition_key(cql, test_keyspace):
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schema = 'p int, v text, primary key (p)'
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with new_test_table(cql, test_keyspace, schema) as table:
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with new_materialized_view(cql, table, '*', 'v, p', 'v is not null and p is not null') as mv:
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cql.execute(f"INSERT INTO {table} (p,v) VALUES (123, '')")
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# Note that because cql-pytest runs on a single node, view
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# updates are synchronous, and we can read the view immediately
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# without retrying. In a general setup, this test would require
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# retries.
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# The view row with the empty partition key should exist.
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# In #9375, this failed in Scylla:
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assert list(cql.execute(f"SELECT * FROM {mv}")) == [('', 123)]
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# Verify that we can flush an sstable with just an one partition
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# with an empty-string key (in the past we had a summary-file
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# sanity check preventing this from working).
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nodetool.flush(cql, mv)
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# Reproducer for issue #9450 - when a view's key column name is a (quoted)
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# keyword, writes used to fail because they generated internally broken CQL
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# with the column name not quoted.
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def test_mv_quoted_column_names(cql, test_keyspace):
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for colname in ['"dog"', '"Dog"', 'DOG', '"to"', 'int']:
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with new_test_table(cql, test_keyspace, f'p int primary key, {colname} int') as table:
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with new_materialized_view(cql, table, '*', f'{colname}, p', f'{colname} is not null and p is not null') as mv:
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cql.execute(f'INSERT INTO {table} (p, {colname}) values (1, 2)')
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# Validate that not only the write didn't fail, it actually
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# write the right thing to the view. NOTE: on a single-node
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# Scylla, view update is synchronous so we can just read and
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# don't need to wait or retry.
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assert list(cql.execute(f'SELECT * from {mv}')) == [(2, 1)]
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# Same as test_mv_quoted_column_names above (reproducing issue #9450), just
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# check *view building* - i.e., pre-existing data in the base table that
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# needs to be copied to the view. The view building cannot return an error
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# to the user, but can fail to write the desired data into the view.
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def test_mv_quoted_column_names_build(cql, test_keyspace):
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for colname in ['"dog"', '"Dog"', 'DOG', '"to"', 'int']:
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with new_test_table(cql, test_keyspace, f'p int primary key, {colname} int') as table:
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cql.execute(f'INSERT INTO {table} (p, {colname}) values (1, 2)')
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with new_materialized_view(cql, table, '*', f'{colname}, p', f'{colname} is not null and p is not null') as mv:
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# When Scylla's view builder fails as it did in issue #9450,
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# there is no way to tell this state apart from a view build
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# that simply hasn't completed (besides looking at the logs,
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# which we don't). This means, unfortunately, that a failure
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# of this test is slow - it needs to wait for a timeout.
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start_time = time.time()
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while time.time() < start_time + 30:
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if list(cql.execute(f'SELECT * from {mv}')) == [(2, 1)]:
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break
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assert list(cql.execute(f'SELECT * from {mv}')) == [(2, 1)]
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# The previous test (test_mv_empty_string_partition_key) verifies that a
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# row with an empty-string partition key can appear in the view. This was
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# checked with a full-table scan. This test is about reading this one
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# view partition individually, with WHERE v=''.
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# Surprisingly, Cassandra does NOT allow to SELECT this specific row
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# individually - "WHERE v=''" is not allowed when v is the partition key
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# (even of a view). We consider this to be a Cassandra bug - it doesn't
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# make sense to allow the user to add a row and to see it in a full-table
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# scan, but not to query it individually. This is why we mark this test as
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# a Cassandra bug and want Scylla to pass it.
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# Reproduces issue #9375 and #9352.
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def test_mv_empty_string_partition_key_individual(cassandra_bug, cql, test_keyspace):
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schema = 'p int, v text, primary key (p)'
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with new_test_table(cql, test_keyspace, schema) as table:
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with new_materialized_view(cql, table, '*', 'v, p', 'v is not null and p is not null') as mv:
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# Insert a bunch of (p,v) rows. One of the v's is the empty
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# string, which we would like to test, but let's insert more
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# rows to make it more likely to exercise various possibilities
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# of token ordering (see #9352).
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rows = [[123, ''], [1, 'dog'], [2, 'cat'], [700, 'hello'], [3, 'horse']]
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for row in rows:
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cql.execute(f"INSERT INTO {table} (p,v) VALUES ({row[0]}, '{row[1]}')")
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# Note that because cql-pytest runs on a single node, view
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# updates are synchronous, and we can read the view immediately
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# without retrying. In a general setup, this test would require
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# retries.
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# Check that we can read the individual partition with the
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# empty-string key:
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assert list(cql.execute(f"SELECT * FROM {mv} WHERE v=''")) == [('', 123)]
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# The SELECT above works from cache. However, empty partition
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# keys also used to be special-cased and be buggy when reading
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# and writing sstables, so let's verify that the empty partition
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# key can actually be written and read from disk, by forcing a
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# memtable flush and bypassing the cache on read.
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# In the past Scylla used to fail this flush because the sstable
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# layer refused to write empty partition keys to the sstable:
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nodetool.flush(cql, mv)
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# First try a full-table scan, and then try to read the
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# individual partition with the empty key:
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assert set(cql.execute(f"SELECT * FROM {mv} BYPASS CACHE")) == {
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(x[1], x[0]) for x in rows}
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# Issue #9352 used to prevent us finding WHERE v='' here, even
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# when the data is known to exist (the above full-table scan
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# saw it!) and despite the fact that WHERE v='' is parsed
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# correctly because we tested above it works from memtables.
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assert list(cql.execute(f"SELECT * FROM {mv} WHERE v='' BYPASS CACHE")) == [('', 123)]
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# Test that the "IS NOT NULL" clause in the materialized view's SELECT
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# functions as expected - namely, rows which have their would-be view
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# key column unset (aka null) do not get copied into the view.
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def test_mv_is_not_null(cql, test_keyspace):
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schema = 'p int, v text, primary key (p)'
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with new_test_table(cql, test_keyspace, schema) as table:
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with new_materialized_view(cql, table, '*', 'v, p', 'v is not null and p is not null') as mv:
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cql.execute(f"INSERT INTO {table} (p,v) VALUES (123, 'dog')")
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cql.execute(f"INSERT INTO {table} (p,v) VALUES (17, null)")
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# Note that because cql-pytest runs on a single node, view
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# updates are synchronous, and we can read the view immediately
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# without retrying. In a general setup, this test would require
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# retries.
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# The row with 123 should appear in the view, but the row with
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# 17 should not, because v *is* null.
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assert list(cql.execute(f"SELECT * FROM {mv}")) == [('dog', 123)]
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# The view row should disappear and reappear if its key is
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# changed to null and back in the base table:
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cql.execute(f"UPDATE {table} SET v=null WHERE p=123")
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assert list(cql.execute(f"SELECT * FROM {mv}")) == []
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cql.execute(f"UPDATE {table} SET v='cat' WHERE p=123")
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assert list(cql.execute(f"SELECT * FROM {mv}")) == [('cat', 123)]
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cql.execute(f"DELETE v FROM {table} WHERE p=123")
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assert list(cql.execute(f"SELECT * FROM {mv}")) == []
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# Refs #10851. The code used to create a wildcard selection for all columns,
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# which erroneously also includes static columns if such are present in the
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# base table. Currently views only operate on regular columns and the filtering
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# code assumes that. Once we implement static column support for materialized
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# views, this test case will be a nice regression test to ensure that everything still
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# works if the static columns are *not* used in the view.
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# This test goes over all combinations of filters for partition, clustering and regular
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# base columns.
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def test_filter_with_unused_static_column(cql, test_keyspace, scylla_only):
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schema = 'p int, c int, v int, s int static, primary key (p,c)'
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with new_test_table(cql, test_keyspace, schema) as table:
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for p_condition in ['p = 42', 'p IS NOT NULL']:
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for c_condition in ['c = 43', 'c IS NOT NULL']:
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for v_condition in ['v = 44', 'v IS NOT NULL']:
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where = f"{p_condition} AND {c_condition} AND {v_condition}"
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with new_materialized_view(cql, table, select='p,c,v', pk='p,c,v', where=where) as mv:
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cql.execute(f"INSERT INTO {table} (p,c,v) VALUES (42,43,44)")
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cql.execute(f"INSERT INTO {table} (p,c,v) VALUES (1,2,3)")
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expected = [(42,43,44)] if '4' in where else [(42,43,44),(1,2,3)]
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assert list(cql.execute(f"SELECT * FROM {mv}")) == expected
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# Ensure that we don't allow materialized views which contain static rows.
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# Neither Cassandra nor Scylla support this at the moment.
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def test_static_columns_are_disallowed(cql, test_keyspace):
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schema = 'p int, c int, v int, s int static, primary key (p,c)'
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with new_test_table(cql, test_keyspace, schema) as table:
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# Case 1: 's' not in primary key
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mv = unique_name()
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try:
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with pytest.raises(InvalidRequest, match="[Ss]tatic column"):
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cql.execute(f"CREATE MATERIALIZED VIEW {test_keyspace}.{mv} AS SELECT p, s FROM {table} PRIMARY KEY (p)")
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finally:
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cql.execute(f"DROP MATERIALIZED VIEW IF EXISTS {test_keyspace}.{mv}")
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# Case 2: 's' in primary key
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mv = unique_name()
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try:
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with pytest.raises(InvalidRequest, match="[Ss]tatic column"):
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cql.execute(f"CREATE MATERIALIZED VIEW {test_keyspace}.{mv} AS SELECT p, s FROM {table} WHERE s IS NOT NULL PRIMARY KEY (s, p)")
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finally:
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cql.execute(f"DROP MATERIALIZED VIEW IF EXISTS {test_keyspace}.{mv}")
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# IS_NOT operator can only be used in the context of materialized view creation and it must be of the form IS NOT NULL.
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# Trying to do something like IS NOT 42 should fail.
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# The error is a SyntaxException because Scylla and Cassandra check this during parsing.
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def test_is_not_operator_must_be_null(cql, test_keyspace):
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schema = 'p int PRIMARY KEY'
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mv = unique_name()
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with new_test_table(cql, test_keyspace, schema) as table:
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try:
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with pytest.raises(SyntaxException, match="NULL"):
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cql.execute(f"CREATE MATERIALIZED VIEW {test_keyspace}.{mv} AS SELECT * FROM {table} WHERE p IS NOT 42 PRIMARY KEY (p)")
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finally:
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cql.execute(f"DROP MATERIALIZED VIEW IF EXISTS {test_keyspace}.{mv}")
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# The IS NOT NULL operator was first added to Cassandra and Scylla for use
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# just in key columns in materialized views. It was not supported in general
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# filters in SELECT (see issue #8517), and in particular cannot be used in
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# a materialized-view definition as a filter on non-key columns. However,
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# if this usage is not allowed, we expect to see a clear error and not silently
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# ignoring the IS NOT NULL condition as happens in issue #10365.
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#
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# NOTE: if issue #8517 (IS NOT NULL in filters) is implemented, we will need to
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# replace this test by a test that checks that the filter works as expected,
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# both in ordinary base-table SELECT and in materialized-view definition.
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def test_is_not_null_forbidden_in_filter(cql, test_keyspace, cassandra_bug):
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with new_test_table(cql, test_keyspace, 'p int primary key, xyz int') as table:
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# Check that "IS NOT NULL" is not supported in a regular (base table)
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# SELECT filter. Cassandra reports an InvalidRequest: "Unsupported
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# restriction: xyz IS NOT NULL". In Scylla the message is different:
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# "restriction '(xyz) IS NOT { null }' is only supported in materialized
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# view creation".
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#
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with pytest.raises(InvalidRequest, match="xyz"):
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cql.execute(f'SELECT * FROM {table} WHERE xyz IS NOT NULL ALLOW FILTERING')
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# Check that "xyz IS NOT NULL" is also not supported in a
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# materialized-view definition (where xyz is not a key column)
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# Reproduces #8517
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mv = unique_name()
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try:
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with pytest.raises(InvalidRequest, match="xyz"):
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cql.execute(f"CREATE MATERIALIZED VIEW {test_keyspace}.{mv} AS SELECT * FROM {table} WHERE p IS NOT NULL AND xyz IS NOT NULL PRIMARY KEY (p)")
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# There is no need to continue the test - if the CREATE
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# MATERIALIZED VIEW above succeeded, it is already not what we
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# expect without #8517. However, let's demonstrate that it's
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# even worse - not only does the "xyz IS NOT NULL" not generate
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# an error, it is outright ignored and not used in the filter.
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# If it weren't ignored, it should filter out partition 124
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# in the following example:
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cql.execute(f"INSERT INTO {table} (p,xyz) VALUES (123, 456)")
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cql.execute(f"INSERT INTO {table} (p) VALUES (124)")
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assert sorted(list(cql.execute(f"SELECT p FROM {test_keyspace}.{mv}")))==[(123,)]
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finally:
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cql.execute(f"DROP MATERIALIZED VIEW IF EXISTS {test_keyspace}.{mv}")
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# Test that a view can be altered with synchronous_updates property and that
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# the synchronous updates code path is then reached for such view.
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# The synchronous_updates feature is a ScyllaDB extension, so this is a
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# scylla_only test.
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def test_mv_synchronous_updates(cql, test_keyspace, scylla_only):
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schema = 'p int, v text, primary key (p)'
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with new_test_table(cql, test_keyspace, schema) as table:
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with new_materialized_view(cql, table, '*', 'v, p', 'v is not null and p is not null') as sync_mv, \
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new_materialized_view(cql, table, '*', 'v, p', 'v is not null and p is not null') as async_mv, \
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new_materialized_view(cql, table, '*', 'v,p', 'v is not null and p is not null', extra='with synchronous_updates = true') as sync_mv_from_the_start, \
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new_materialized_view(cql, table, '*', 'v,p', 'v is not null and p is not null', extra='with synchronous_updates = true') as async_mv_altered:
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# Make one view synchronous
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cql.execute(f"ALTER MATERIALIZED VIEW {sync_mv} WITH synchronous_updates = true")
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# Make another one asynchronous
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cql.execute(f"ALTER MATERIALIZED VIEW {async_mv_altered} WITH synchronous_updates = false")
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# Execute a query and inspect its tracing info
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res = cql.execute(f"INSERT INTO {table} (p,v) VALUES (123, 'dog')", trace=True)
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trace = res.get_query_trace()
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wanted_trace1 = f"Forcing {sync_mv} view update to be synchronous"
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wanted_trace2 = f"Forcing {sync_mv_from_the_start} view update to be synchronous"
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unwanted_trace1 = f"Forcing {async_mv} view update to be synchronous"
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unwanted_trace2 = f"Forcing {async_mv_altered} view update to be synchronous"
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wanted_traces_were_found = [False, False]
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for event in trace.events:
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assert unwanted_trace1 not in event.description
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assert unwanted_trace2 not in event.description
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if wanted_trace1 in event.description:
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wanted_traces_were_found[0] = True
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if wanted_trace2 in event.description:
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wanted_traces_were_found[1] = True
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assert all(wanted_traces_were_found)
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# Reproduces #8627:
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# Whereas regular columns values are limited in size to 2GB, key columns are
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# limited to 64KB. This means that if a certain column is regular in the base
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# table but a key in one of its views, we cannot write to this regular column
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# an over-64KB value. Ideally, such a write should fail cleanly with an
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# InvalidQuery.
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# But today, neither Cassandra nor Scylla does this correctly. Both do not
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# detect the problem at the coordinator level, and both send the writes to the
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# replicas and fail the view update in each replica. The user's write may or
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# may not fail depending on whether the view update is done synchronously
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# (Scylla, sometimes) or asynchrhonously (Casandra). But even in the failure
|
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# case the failure does not explain why the replica writes failed - the only
|
|
# message about a key being too long appears in the log.
|
|
# Note that the same issue also applies to secondary indexes, and this is
|
|
# tested in test_secondary_index.py.
|
|
@pytest.mark.xfail(reason="issue #8627")
|
|
def test_oversized_base_regular_view_key(cql, test_keyspace, cassandra_bug):
|
|
with new_test_table(cql, test_keyspace, 'p int primary key, v text') as table:
|
|
with new_materialized_view(cql, table, select='*', pk='v,p', where='v is not null and p is not null') as mv:
|
|
big = 'x'*66536
|
|
with pytest.raises(InvalidRequest, match='size'):
|
|
cql.execute(f"INSERT INTO {table}(p,v) VALUES (1,'{big}')")
|
|
# Ideally, the entire write operation should be considered
|
|
# invalid, and no part of it will be done. In particular, the
|
|
# base write will also not happen.
|
|
assert [] == list(cql.execute(f"SELECT * FROM {table} WHERE p=1"))
|
|
|
|
# Reproduces #8627:
|
|
# Same as test_oversized_base_regular_view_key above, just check *view
|
|
# building*- i.e., pre-existing data in the base table that needs to be
|
|
# copied to the view. The view building cannot return an error to the user,
|
|
# but we do expect it to skip the problematic row and continue to complete
|
|
# the rest of the view build.
|
|
@pytest.mark.xfail(reason="issue #8627")
|
|
# This test currently breaks the build (it repeats a failing build step,
|
|
# and never complete) and we cannot quickly recognize this failure, so
|
|
# to avoid a very slow failure, we currently "skip" this test.
|
|
@pytest.mark.skip(reason="issue #8627, fails very slow")
|
|
def test_oversized_base_regular_view_key_build(cql, test_keyspace, cassandra_bug):
|
|
with new_test_table(cql, test_keyspace, 'p int primary key, v text') as table:
|
|
# No materialized view yet - a "big" value in v is perfectly fine:
|
|
stmt = cql.prepare(f'INSERT INTO {table} (p,v) VALUES (?, ?)')
|
|
for i in range(30):
|
|
cql.execute(stmt, [i, str(i)])
|
|
big = 'x'*66536
|
|
cql.execute(stmt, [30, big])
|
|
assert [(30,big)] == list(cql.execute(f'SELECT * FROM {table} WHERE p=30'))
|
|
# Add a materialized view with v as the new key. The view build,
|
|
# copying data from the base table to the view, should start promptly.
|
|
with new_materialized_view(cql, table, select='*', pk='v,p', where='v is not null and p is not null') as mv:
|
|
# If Scylla's view builder hangs or stops, there is no way to
|
|
# tell this state apart from a view build that simply hasn't
|
|
# completed yet (besides looking at the logs, which we don't).
|
|
# This means, unfortunately, that a failure of this test is slow -
|
|
# it needs to wait for a timeout.
|
|
start_time = time.time()
|
|
while time.time() < start_time + 30:
|
|
results = set(list(cql.execute(f'SELECT * from {mv}')))
|
|
# The oversized "big" cannot be a key in the view, so
|
|
# shouldn't be in results:
|
|
assert not (big, 30) in results
|
|
print(results)
|
|
# The rest of the items in the base table should be in
|
|
# the view:
|
|
if results == {(str(i), i) for i in range(30)}:
|
|
break
|
|
time.sleep(0.1)
|
|
assert results == {(str(i), i) for i in range(30)}
|
|
|
|
# Reproduces #11668
|
|
# When the view builder resumes building a partition, it reuses the reader
|
|
# used from the previous step but re-creates the compactor. This means that any
|
|
# range tombstone changes active at the time of suspending the step, have to be
|
|
# explicitly re-opened on when resuming. Without that, already deleted base rows
|
|
# can be resurrected as demonstrated by this test.
|
|
# The view-builder suspends processing a base-table after
|
|
# `view_builder::batch_size` (that is 128) rows. So in this test we create a
|
|
# table which has at least 2X that many rows and add a range tombstone so that
|
|
# it covers half of the rows (even rows are covered why odd rows aren't).
|
|
def test_view_builder_suspend_with_active_range_tombstone(cql, test_keyspace, scylla_only):
|
|
with new_test_table(cql, test_keyspace, "pk int, ck int, v int, PRIMARY KEY(pk, ck)", "WITH compaction = {'class': 'NullCompactionStrategy'}") as table:
|
|
stmt = cql.prepare(f'INSERT INTO {table} (pk, ck, v) VALUES (?, ?, ?)')
|
|
|
|
# sstable 1 - even rows
|
|
for ck in range(0, 512, 2):
|
|
cql.execute(stmt, (0, ck, ck))
|
|
nodetool.flush(cql, table)
|
|
|
|
# sstable 2 - odd rows and a range tombstone covering even rows
|
|
# we need two sstables so memtable doesn't compact away the shadowed rows
|
|
cql.execute(f"DELETE FROM {table} WHERE pk = 0 AND ck >= 0 AND ck < 512")
|
|
for ck in range(1, 512, 2):
|
|
cql.execute(stmt, (0, ck, ck))
|
|
nodetool.flush(cql, table)
|
|
|
|
# we should not see any even rows here - they are covered by the range tombstone
|
|
res = [r.ck for r in cql.execute(f"SELECT ck FROM {table} WHERE pk = 0")]
|
|
assert res == list(range(1, 512, 2))
|
|
|
|
with new_materialized_view(cql, table, select='*', pk='v,pk,ck', where='v is not null and pk is not null and ck is not null') as mv:
|
|
start_time = time.time()
|
|
while time.time() < start_time + 30:
|
|
res = sorted([r.v for r in cql.execute(f"SELECT * FROM {mv}")])
|
|
if len(res) >= 512/2:
|
|
break
|
|
time.sleep(0.1)
|
|
# again, we should not see any even rows in the materialized-view,
|
|
# they are covered with a range tombstone in the base-table
|
|
assert res == list(range(1, 512, 2))
|
|
|
|
# A variant of the above using a partition-tombstone, which is also lost similar
|
|
# to range tombstones.
|
|
def test_view_builder_suspend_with_partition_tombstone(cql, test_keyspace, scylla_only):
|
|
with new_test_table(cql, test_keyspace, "pk int, ck int, v int, PRIMARY KEY(pk, ck)", "WITH compaction = {'class': 'NullCompactionStrategy'}") as table:
|
|
stmt = cql.prepare(f'INSERT INTO {table} (pk, ck, v) VALUES (?, ?, ?)')
|
|
|
|
# sstable 1 - even rows
|
|
for ck in range(0, 512, 2):
|
|
cql.execute(stmt, (0, ck, ck))
|
|
nodetool.flush(cql, table)
|
|
|
|
# sstable 2 - odd rows and a partition covering even rows
|
|
# we need two sstables so memtable doesn't compact away the shadowed rows
|
|
cql.execute(f"DELETE FROM {table} WHERE pk = 0")
|
|
for ck in range(1, 512, 2):
|
|
cql.execute(stmt, (0, ck, ck))
|
|
nodetool.flush(cql, table)
|
|
|
|
# we should not see any even rows here - they are covered by the partition tombstone
|
|
res = [r.ck for r in cql.execute(f"SELECT ck FROM {table} WHERE pk = 0")]
|
|
assert res == list(range(1, 512, 2))
|
|
|
|
with new_materialized_view(cql, table, select='*', pk='v,pk,ck', where='v is not null and pk is not null and ck is not null') as mv:
|
|
start_time = time.time()
|
|
while time.time() < start_time + 30:
|
|
res = sorted([r.v for r in cql.execute(f"SELECT * FROM {mv}")])
|
|
if len(res) >= 512/2:
|
|
break
|
|
time.sleep(0.1)
|
|
# again, we should not see any even rows in the materialized-view,
|
|
# they are covered with a partition tombstone in the base-table
|
|
assert res == list(range(1, 512, 2))
|
|
|
|
# Test when IS NOT NULL is required, vs. not required, for the key columns
|
|
# of a materialized view WHERE clause.
|
|
# In general, the user needs to add a IS NOT NULL for each and every key
|
|
# column of the view in the view's WHERE clause, to emphasize that when
|
|
# a row has a null value for that column - the row will be missing from
|
|
# the view (because null key columns are not allowed).
|
|
# However, one can argue that if one of the view's key columns was already
|
|
# a base key column, then it is already known that this column cannot ever
|
|
# be null, so it is pointless to require the "IS NOT NULL". However,
|
|
# Cassandra still requires "IS NOT NULL" on any column - even base key
|
|
# columns.
|
|
# This test reproduces issue issue #11979, that Scylla used to require
|
|
# IS NOT NULL inconsistently.
|
|
@pytest.mark.xfail(reason="issue #11979")
|
|
def test_is_not_null_requirement(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, v int, primary key (p, c)') as table:
|
|
# missing "v is not null":
|
|
with pytest.raises(InvalidRequest, match="IS NOT NULL"):
|
|
with new_materialized_view(cql, table, select='*', pk='p,c,v', where='p is not null and c is not null') as mv:
|
|
pass
|
|
# missing "c is not null":
|
|
with pytest.raises(InvalidRequest, match="IS NOT NULL"):
|
|
with new_materialized_view(cql, table, select='*', pk='p,c,v', where='v is not null and p is not null') as mv:
|
|
pass
|
|
# missing "p is not null":
|
|
# This check reproduces issue #11979:
|
|
with pytest.raises(InvalidRequest, match="IS NOT NULL"):
|
|
with new_materialized_view(cql, table, select='*', pk='p,c,v', where='c is not null and v is not null') as mv:
|
|
pass
|
|
# Similar test, with composite keys
|
|
with new_test_table(cql, test_keyspace, 'p1 int, p2 int, c1 int, c2 int, v int, primary key ((p1, p2), c1, c2)') as table:
|
|
# missing "p1 is not null":
|
|
with pytest.raises(InvalidRequest, match="IS NOT NULL"):
|
|
with new_materialized_view(cql, table, select='*', pk='p1,p2,c1,c2,v', where='p2 is not null and c1 is not null and c2 is not null and v is not null') as mv:
|
|
pass
|
|
# missing "p2 is not null":
|
|
with pytest.raises(InvalidRequest, match="IS NOT NULL"):
|
|
with new_materialized_view(cql, table, select='*', pk='p1,p2,c1,c2,v', where='p1 is not null and c1 is not null and c2 is not null and v is not null') as mv:
|
|
pass
|
|
# missing "c1 is not null":
|
|
with pytest.raises(InvalidRequest, match="IS NOT NULL"):
|
|
with new_materialized_view(cql, table, select='*', pk='p1,p2,c1,c2,v', where='p1 is not null and p2 is not null and c2 is not null and v is not null') as mv:
|
|
pass
|
|
# missing "c2 is not null":
|
|
with pytest.raises(InvalidRequest, match="IS NOT NULL"):
|
|
with new_materialized_view(cql, table, select='*', pk='p1,p2,c1,c2,v', where='p1 is not null and p2 is not null and c1 is not null and v is not null') as mv:
|
|
pass
|
|
# missing "v is not null":
|
|
with pytest.raises(InvalidRequest, match="IS NOT NULL"):
|
|
with new_materialized_view(cql, table, select='*', pk='p1,p2,c1,c2,v', where='p1 is not null and p2 is not null and c1 is not null and c2 is not null') as mv:
|
|
pass
|
|
|
|
# Reproducer for issue #11542 and #10026: We have a table with with a
|
|
# materialized view with a filter and some data, at which point we modify
|
|
# the base table (e.g., add some silly comment) and then try to modify the
|
|
# data. The last modification used to fail, logging "Column definition v
|
|
# does not match any column in the query selection".
|
|
# The same test without the silly base-table modification works, and so does
|
|
# the same test without the filter in the materialized view that uses the
|
|
# base-regular column v. So does the same test without pre-modification data.
|
|
#
|
|
# This test is Scylla-only because Cassandra does not support filtering
|
|
# on a base-regular column v that is only a key column in the view.
|
|
def test_view_update_and_alter_base(cql, test_keyspace, scylla_only):
|
|
with new_test_table(cql, test_keyspace, 'p int primary key, v int') as table:
|
|
with new_materialized_view(cql, table, '*', 'v, p', 'v >= 0 and p is not null') as mv:
|
|
cql.execute(f'INSERT INTO {table} (p,v) VALUES (1,1)')
|
|
# In our tests, MV writes are synchronous, so we can read
|
|
# immediately
|
|
assert len(list(cql.execute(f"SELECT v from {mv}"))) == 1
|
|
# Alter the base table, with a silly comment change that doesn't
|
|
# change anything important - but still the base schema changes.
|
|
cql.execute(f"ALTER TABLE {table} WITH COMMENT = '{unique_name()}'")
|
|
# Try to modify an item. This failed in #11542.
|
|
cql.execute(f'UPDATE {table} SET v=-1 WHERE p=1')
|
|
assert len(list(cql.execute(f"SELECT v from {mv}"))) == 0
|
|
|
|
# Reproducer for issue #12297, reproducing a specific way in which a view
|
|
# table could be made inconsistent with the base table:
|
|
# The test writes 500 rows to one partition in a base table, and then uses
|
|
# USING TIMESTAMP with the right value to cause a base partition deletion
|
|
# which deletes not the entire partition but just its last 50 rows. As the
|
|
# 50 rows of the base partition get deleted, we expect 50 rows from the
|
|
# view table to also get deleted - but bug #12297 was that this wasn't
|
|
# happening - rather, all rows remained in the view.
|
|
# The bug cannot be reproduced with 100 rows (and deleting the last 10)
|
|
# but 113 rows (and 101 rows after deleting the last 12) does reproduce
|
|
# it. Reproducing the bug also required a setup where USING TIMESTAMP
|
|
# deleted the *last* rows - using it to delete the *first* rows did not
|
|
# have a bug (the view rows were deleted fine).
|
|
@pytest.mark.parametrize("size", [100, 113, 500])
|
|
def test_long_skipped_view_update_delete_with_timestamp(cql, test_keyspace, size):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)') as table:
|
|
with new_materialized_view(cql, table, '*', 'p, x, c', 'p is not null and x is not null and c is not null') as mv:
|
|
# Write size rows with c=0..(size-1). Because the iteration is in
|
|
# reverse order, the first row in clustering order (c=0) will
|
|
# have the latest write timestamp.
|
|
for i in reversed(range(size)):
|
|
cql.execute(f'INSERT INTO {table} (p,c,x,y) VALUES (1,{i},{i},{i})')
|
|
assert list(cql.execute(f"SELECT c FROM {table} WHERE p = 1")) == list(cql.execute(f"SELECT c FROM {mv} WHERE p = 1"))
|
|
# Get the timestamp of the size*0.9th item. Because we wrote items
|
|
# in reverse, items 0.9-1.0*size all have earlier timestamp than
|
|
# that.
|
|
t = list(cql.execute(f"SELECT writetime(y) FROM {table} WHERE p = 1 and c = {int(size*0.9)}"))[0].writetime_y
|
|
cql.execute(f'DELETE FROM {table} USING TIMESTAMP {t} WHERE p=1')
|
|
# After the deletion we expect to see size*0.9 rows remaining
|
|
# (timestamp ties cannot happen for separate writes, if they
|
|
# did we could have a bit less), but most importantly, the view
|
|
# should have exactly the same rows.
|
|
assert list(cql.execute(f"SELECT c FROM {table} WHERE p = 1")) == list(cql.execute(f"SELECT c FROM {mv} WHERE p = 1"))
|
|
|
|
# Same test as above, just that in this version the view partition key is
|
|
# different from the base's, so we can be sure that Scylla needs to go
|
|
# through the loop of deleting many view rows and cannot delete an entire
|
|
# view partition in one fell swoop. In the above test, Scylla *may* contain
|
|
# such an optimization (currently it doesn't), so it may reach a different
|
|
# code path.
|
|
def test_long_skipped_view_update_delete_with_timestamp2(cql, test_keyspace):
|
|
size = 200
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)') as table:
|
|
with new_materialized_view(cql, table, '*', 'x, p, c', 'p is not null and x is not null and c is not null') as mv:
|
|
for i in reversed(range(size)):
|
|
cql.execute(f'INSERT INTO {table} (p,c,x,y) VALUES (1,{i},{i},{i})')
|
|
assert list(cql.execute(f"SELECT c FROM {table}")) == sorted(list(cql.execute(f"SELECT c FROM {mv}")))
|
|
t = list(cql.execute(f"SELECT writetime(y) FROM {table} WHERE p = 1 and c = {int(size*0.9)}"))[0].writetime_y
|
|
cql.execute(f'DELETE FROM {table} USING TIMESTAMP {t} WHERE p=1')
|
|
assert list(cql.execute(f"SELECT c FROM {table}")) == sorted(list(cql.execute(f"SELECT c FROM {mv}")))
|
|
|
|
# Another, more fundamental, reproducer for issue #12297 where a certain
|
|
# modification to a base partition modifying more than 100 rows was not
|
|
# applied to the view beyond the 100th row.
|
|
# The test above, test_long_skipped_view_update_delete_with_timestamp was one
|
|
# such specific case, which involved a partition tombstone and a specific
|
|
# choice of timestamp which causes the first 100 rows to NOT be changed.
|
|
# In this test we show that the bug is not just about do-nothing tombstones:
|
|
# In any base modification which involves more than 100 rows, if the first
|
|
# 100 rows don't change the view (as decided by the can_skip_view_updates()
|
|
# function), the other rows are wrongly skipped at well and not applied to
|
|
# the view!
|
|
# The specific case we use here is an update that sets some irrelevant
|
|
# (not-selected-by-the-view) column y on 200 rows, and additionally writes
|
|
# a new row as the 201st row. With bug #12297, that 201st row will be
|
|
# missing in the view.
|
|
def test_long_skipped_view_update_irrelevant_column(cql, test_keyspace):
|
|
size = 200
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)') as table:
|
|
# Note that column "y" is not selected by the materialized view
|
|
with new_materialized_view(cql, table, 'p, x, c', 'p, x, c', 'p is not null and x is not null and c is not null') as mv:
|
|
for i in range(size):
|
|
cql.execute(f'INSERT INTO {table} (p,c,x,y) VALUES (1,{i},{i},{i})')
|
|
# In a single batch (a single mutation), update "y" column in all
|
|
# 'size' existing rows, plus add one new row in the last position
|
|
# (the partition is sorted by the "c" column). The first 'size'
|
|
# UPDATEs can be skipped in the view (because y isn't selected),
|
|
# but the last INSERT can't be skipped - it really adds a new row.
|
|
cmd = 'BEGIN BATCH '
|
|
for i in range(size):
|
|
cmd += f'UPDATE {table} SET y=7 where p=1 and c={i}; '
|
|
cmd += f'INSERT INTO {table} (p,c,x,y) VALUES (1,{size+1},{size+1},{size+1}); '
|
|
cmd += 'APPLY BATCH;'
|
|
cql.execute(cmd)
|
|
# We should now have the same size+1 rows in both base and view
|
|
assert list(cql.execute(f"SELECT c FROM {table} WHERE p = 1")) == list(cql.execute(f"SELECT c FROM {mv} WHERE p = 1"))
|
|
|
|
# After the previous tests checked elaborate conditions where modifying a
|
|
# base-table partition resulted in many skipped view updates, let's also
|
|
# check the more basic situation where the base-table partition modification
|
|
# (in this case, a deletion) result in many view-table updates, and all
|
|
# of them should happen even if the code needs to do it internally in
|
|
# several batches of 100 (for example).
|
|
def test_mv_long_delete(cql, test_keyspace):
|
|
size = 300
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)') as table:
|
|
with new_materialized_view(cql, table, '*', 'p, x, c', 'p is not null and x is not null and c is not null') as mv:
|
|
for i in range(size):
|
|
cql.execute(f'INSERT INTO {table} (p,c,x,y) VALUES (1,{i},{i},{i})')
|
|
cql.execute(f'DELETE FROM {table} WHERE p=1')
|
|
assert list(cql.execute(f"SELECT c FROM {table} WHERE p = 1")) == []
|
|
assert list(cql.execute(f"SELECT c FROM {mv} WHERE p = 1")) == []
|
|
|
|
# Several tests for how "CLUSTERING ORDER BY" interacts with materialized
|
|
# views:
|
|
|
|
# In Cassandra, when a base table has a reversed-order clustering column and
|
|
# this column is used in a materialized view, its order in the view inherits
|
|
# the same reversed sort order it had in the base table.
|
|
# Reproduces #12308
|
|
@pytest.mark.xfail(reason="issue #12308")
|
|
def test_mv_inherit_clustering_order(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)', 'with clustering order by (c DESC)') as table:
|
|
# note no explicit clustering order on c in the materialized view:
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null') as mv:
|
|
for i in range(4):
|
|
cql.execute(f'INSERT INTO {table} (p,c,x,y) VALUES (1,{i},{i},{i})')
|
|
# The base table's clustering order is reversed, and it should
|
|
# also be in the view (at least, it's so in Cassandra).
|
|
assert list(cql.execute(f'SELECT y from {table}')) == [(3,),(2,),(1,),(0,)]
|
|
assert list(cql.execute(f'SELECT y from {mv}')) == [(3,),(2,),(1,),(0,)]
|
|
|
|
# When a materialized view specification declares the clustering keys of
|
|
# they view, they default to the base table's clustering order (see test
|
|
# above), but the order can be overridden by an explicit "with clustering
|
|
# order by" in the materialized view definition:
|
|
def test_mv_override_clustering_order_1(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)', 'with clustering order by (c DESC)') as table:
|
|
# explicitly reverse the clustering order of "c" to be ascending.
|
|
# note that if we specify c's clustering order, we are also forced
|
|
# to specify x's even though we just want it to be the default:
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by (c ASC, x ASC)') as mv:
|
|
for i in range(4):
|
|
cql.execute(f'INSERT INTO {table} (p,c,x,y) VALUES (1,{i},{i},{i})')
|
|
# The base table's clustering order is descending, but in the view
|
|
# it should be ascending.
|
|
assert list(cql.execute(f'SELECT y from {table}')) == [(3,),(2,),(1,),(0,)]
|
|
assert list(cql.execute(f'SELECT y from {mv}')) == [(0,),(1,),(2,),(3,)]
|
|
|
|
def test_mv_override_clustering_order_2(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)', 'with clustering order by (c ASC)') as table:
|
|
# explicitly reverse the clustering order of "c" to be descending.
|
|
# note that if we specify c's clustering order, we are also forced
|
|
# to specify x's even though we just want it to be the default:
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by (c DESC, x ASC)') as mv:
|
|
for i in range(4):
|
|
cql.execute(f'INSERT INTO {table} (p,c,x,y) VALUES (1,{i},{i},{i})')
|
|
# The base table's clustering order is ascending, but in the view
|
|
# it should be descending.
|
|
assert list(cql.execute(f'SELECT y from {table}')) == [(0,),(1,),(2,),(3,)]
|
|
assert list(cql.execute(f'SELECT y from {mv}')) == [(3,),(2,),(1,),(0,)]
|
|
|
|
# Another test for CLUSTERING ORDER BY, using quoted and unquoted column
|
|
# names and checking they are matched properly
|
|
def test_mv_override_clustering_order_quoted(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, "Hello" int, primary key (p,c)') as table:
|
|
# X and "x" are the same as x:
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by (c DESC, X ASC)') as mv:
|
|
pass
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by (c DESC, "x" ASC)') as mv:
|
|
pass
|
|
# But "Hello" is not the same as "HELLO" or hello
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, "Hello"', 'p is not null and c is not null and "Hello" is not null', 'with clustering order by (c DESC, hello ASC)') as mv:
|
|
pass
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, "Hello"', 'p is not null and c is not null and "Hello" is not null', 'with clustering order by (c DESC, "HELLO" ASC)') as mv:
|
|
pass
|
|
|
|
# Cassandra requires that if we specify WITH CLUSTERING ORDER BY in the
|
|
# materialized view definition, it must mention all clustering key columns
|
|
# defined in the view's PRIMARY KEY, in that same order. If the columns are
|
|
# mis-ordered or one is missing, the statement is rejected with the message
|
|
# "Clustering key columns must exactly match columns in CLUSTERING ORDER BY
|
|
# directive". The reason for this rejection is that CLUSTERING ORDER BY
|
|
# with a misordered or partial list of clustering columns may wrongly suggest
|
|
# that this list determines the order of clustering columns when comparing
|
|
# them - when in fact the PRIMARY KEY specification controls that order.
|
|
# The following test verifies that these bad WITH CLUSTERING ORDER BY
|
|
# clauses are indeed rejected.
|
|
# Reproduces #12936.
|
|
@pytest.mark.xfail(reason="issue #12936")
|
|
def test_mv_override_clustering_order_bad1(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)') as table:
|
|
# Mis-ordered clustering columns: c,x on PRIMARY KEY, but
|
|
# x,c in WITH CLUSTERING ORDER:
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'WITH CLUSTERING ORDER BY (x ASC, c ASC)') as mv:
|
|
pass
|
|
# Missing clustering columns: c,x on PRIMARY KEY, but
|
|
# x or c in WITH CLUSTERING ORDER:
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'WITH CLUSTERING ORDER BY (c ASC)') as mv:
|
|
pass
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'WITH CLUSTERING ORDER BY (x ASC)') as mv:
|
|
pass
|
|
# Duplicate clustering column: c,x on PRIMARY KEY, but c,x,x
|
|
# (with same or different order for x) in WITH CLUSTERING ORDER:
|
|
for order in ['c ASC, x ASC, x ASC',
|
|
'c ASC, x ASC, x DESC',
|
|
'c ASC, c ASC, x ASC',
|
|
'c ASC, c DESC, x ASC']:
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', f'WITH CLUSTERING ORDER BY ({order})') as mv:
|
|
pass
|
|
|
|
# Cassandra is strict about the WITH CLUSTERING ORDER BY clause in the
|
|
# definition of the materialized view that must, if it exists, list all
|
|
# the view's clustering keys. Scylla was less strict (the above test
|
|
# test_mv_override_clustering_order_bad failed), but in any case we should
|
|
# not allow to list spurious names of non-clustering keys in the CLUSTERING
|
|
# ORDER BY clause. Reproduces #10767.
|
|
def test_mv_override_clustering_order_bad2(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, x int, y int, primary key (p,c)') as table:
|
|
# Only a non-clustering-key column y (clustering key c and x missing):
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by (y DESC)') as mv:
|
|
pass
|
|
# The two clustering key column (c and x) plus a regular column y
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by (c ASC, x ASC, y DESC)') as mv:
|
|
pass
|
|
# The two clustering key column (c and x) plus a partition key p
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by (c ASC, x ASC, p DESC)') as mv:
|
|
pass
|
|
# The two clustering key column (c and x) plus non-existent z
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by (c ASC, x ASC, z DESC)') as mv:
|
|
pass
|
|
# The clustering key column in the base (c) but it's no longer
|
|
# a clustering key column in the view so can't be ordered
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'c, p', 'p is not null and c is not null', 'with clustering order by (c ASC)') as mv:
|
|
pass
|
|
# Check that the case of quoted names is supported correctly,
|
|
# "X" and x are not the same
|
|
with pytest.raises(InvalidRequest, match="CLUSTERING ORDER BY"):
|
|
with new_materialized_view(cql, table, '*', 'p, c, x', 'p is not null and c is not null and x is not null', 'with clustering order by ("X" ASC)') as mv:
|
|
pass
|
|
|
|
# Test views that only refer to the primary key, exercising the invisible
|
|
# empty type columns that are injected into the view schema in order to
|
|
# compute the view row liveness.
|
|
#
|
|
# scylla_only because Cassandra doesn't support synchronous updates.
|
|
def test_mv_with_only_primary_key_rows(scylla_only, cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'id int PRIMARY KEY, v1 int, v2 int') as base:
|
|
# Use a synchronous view so we don't have to worry about races between flush and
|
|
# view updates.
|
|
with new_materialized_view(cql, table=base, select='id', pk='id', where='id IS NOT NULL',
|
|
extra='WITH synchronous_updates = true') as view:
|
|
cql.execute(f'INSERT INTO {base} (id, v1) VALUES (1, 0)')
|
|
cql.execute(f'INSERT INTO {base} (id, v2) VALUES (2, 0)')
|
|
cql.execute(f'INSERT INTO {base} (id) VALUES (3)')
|
|
# The following row is kept alive by the liveness of v1, since it doesn't have a row marker
|
|
cql.execute(f'UPDATE {base} SET v1 = 7 WHERE id = 4')
|
|
nodetool.flush(cql, view)
|
|
assert(set([row.id for row in cql.execute(f'SELECT id FROM {view}')]) == set([1, 2, 3, 4]))
|
|
# Remove that special row 4
|
|
cql.execute(f'DELETE v1 FROM {base} WHERE id = 4')
|
|
nodetool.flush(cql, view)
|
|
assert(set([row.id for row in cql.execute(f'SELECT id FROM {view}')]) == set([1, 2, 3]))
|
|
# We now believe that empty value serialization/deserialization is correct
|
|
|
|
# This test is regression testing added after fixing:
|
|
# https://github.com/scylladb/scylladb/issues/16392 - the gist of the issue is that
|
|
# prepared statements on views are not invalidated when the base table changes.
|
|
def test_mv_prepared_statement_with_altered_base(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'id int PRIMARY KEY, v1 int') as base:
|
|
with new_materialized_view(cql, table=base, select='*', pk='id', where='id IS NOT NULL') as view:
|
|
base_query = cql.prepare(f"SELECT * FROM {base} WHERE id=?")
|
|
view_query = cql.prepare(f"SELECT * FROM {view} WHERE id=?")
|
|
cql.execute(f"INSERT INTO {base} (id,v1) VALUES (0,0)")
|
|
assert cql.execute(base_query,[0]) == cql.execute(view_query,[0])
|
|
cql.execute(f"ALTER TABLE {base} ADD (v2 int)")
|
|
cql.execute(f"INSERT INTO {base} (id,v1,v2) VALUES (1,1,1)")
|
|
assert list(cql.execute(base_query,[1])) == list(cql.execute(view_query,[1]))
|
|
|
|
# A reproducer for issue #17117:
|
|
# When a single base update generates many view updates to the same partition,
|
|
# instead of processing the entire huge partition at once Scylla processes the
|
|
# view updates in chunks of 100 rows each (max_rows_for_view_updates).
|
|
# We had a bug with *range tombstones* which were mis-counted for this limit,
|
|
# and moreover - could cause a chunk to end in the middle of a range
|
|
# tombstone, which causes the range tombstone in this case to be lost and not
|
|
# reach the view.
|
|
# This test is a simple reproducer for this case. Because IN are limited
|
|
# in size to max_clustering_key_restrictions_per_query (100), we use a
|
|
# BATCH in this test to generate more than 100 (max_rows_for_view_updates)
|
|
# view updates from just one mutation.
|
|
def test_many_range_tombstone_base_update(cql, test_keyspace):
|
|
# This test inserts N rows and deletes all of them in one batch.
|
|
N = 234
|
|
# We need two clustering key columns in this test, so that deleting
|
|
# each "WHERE c1=?" will cause a *range* tombstone - which is what
|
|
# we want to reproduce in this test.
|
|
with new_test_table(cql, test_keyspace, 'p int, c1 int, c2 int, primary key (p, c1, c2)') as table:
|
|
# For simplicity, the view is identical to the base. This is good
|
|
# enough and still reproduces the bug. Remember that range tombstones
|
|
# on the base are not copied to the view as-is - they are translated
|
|
# to row tombstones in the view for the specific rows that really
|
|
# exist in the base table.
|
|
with new_materialized_view(cql, table, '*', 'p, c1, c2', 'p is not null and c1 is not null and c2 is not null') as mv:
|
|
insert = cql.prepare(f'INSERT INTO {table} (p, c1, c2) VALUES (?,?,?)')
|
|
# We need all of the rows to end up in the same view
|
|
# partition, so all the deletions will be in the same
|
|
# partition and will be divided into chunks. Hence we'll
|
|
# use the same partition key 42 for all rows:
|
|
p = 42
|
|
for i in range(N):
|
|
cql.execute(insert, [p, i, i])
|
|
# Remove all N rows using N *range* tombstones (deleting based
|
|
# on p,c1 but not c2), all in one write to the base (a batch):
|
|
cmd = 'BEGIN BATCH '
|
|
for i in range(N):
|
|
cmd += f'DELETE FROM {table} WHERE p={p} AND c1={i} '
|
|
cmd += 'APPLY BATCH;'
|
|
cql.execute(cmd)
|
|
# At this point, both base table and view tables should be
|
|
# empty.
|
|
assert [] == list(cql.execute(f'SELECT c1 FROM {table}'))
|
|
assert [] == list(cql.execute(f'SELECT c1 FROM {mv}'))
|
|
|
|
# Another more elaborate reproducer for issue #17117, which is closer to the
|
|
# original use where we encountered this bug. It uses IN instead of BATCH, so
|
|
# it it is limited to deletions of max_clustering_key_restrictions_per_query
|
|
# (100) clustering ranges, but that's enough to reproduce this bug because
|
|
# anything more than 25 reproduced it. The view in this reproducer is also
|
|
# a bit more interesting than in the previous test (the view is not identical
|
|
# to the base, rather it combines several base partitions into one
|
|
# view partition).
|
|
def test_many_range_tombstone_base_update_2(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p1 int, p2 int, c1 int, c2 int, v1 int, v2 int, primary key ((p1,p2),c1,c2)') as table:
|
|
with new_materialized_view(cql, table, '*', '(v1,p2),c1,p1,c2', 'v1 is not null and p2 is not null and c1 is not null and p1 is not null and c2 is not null') as mv:
|
|
insert = cql.prepare(f'INSERT INTO {table} (p1,p2,c1,c2,v1,v2) VALUES (?,?,?,?,?,?)')
|
|
# Insert N items, with:
|
|
# * p1 cycles between NP1 different values.
|
|
# * c1 is unique per item.
|
|
# * p2, c2, v1, and v2, are the same for all items.
|
|
N = 500
|
|
NP1 = 3
|
|
# fixed values:
|
|
p2 = 123
|
|
v1 = 456
|
|
v2 = 678
|
|
c2 = 987
|
|
for i in range(N):
|
|
p1 = i % NP1
|
|
c1 = i
|
|
cql.execute(insert, [p1,p2,c1,c2,v1,v2])
|
|
# Delete slice with prefix p1,p2,c1 for multiple c1's (any c2)
|
|
delete_slices = cql.prepare(f'DELETE FROM {table} WHERE p1=? AND p2=? AND c1 in ?')
|
|
# This test appears fail due to #17117 for any K>25 - the 26th
|
|
# and every multiple of 26th deletion in the batch doesn't reach
|
|
# the view.
|
|
K=80
|
|
for p1 in range(NP1):
|
|
# c1's for this p1 are i's such that i%NP1 = p1.
|
|
# Only take the c1's that are after N//2, to delete
|
|
# only the later half of the items.
|
|
start = N//2
|
|
start -= start % NP1
|
|
c1s = range(start + p1, N, NP1)
|
|
# split c1s into chunks of length K
|
|
chunks = []
|
|
for x in range(0, len(c1s), K):
|
|
slice_item = slice(x, x + K, 1)
|
|
chunks.append(c1s[slice_item])
|
|
for chunk in chunks:
|
|
cql.execute(delete_slices, [p1, p2, chunk])
|
|
# The deletions above are pretty hard to follow, but no matter
|
|
# what we deleted above, it should have been deleted from
|
|
# both base and view. If the base and view differ, we have a bug.
|
|
list_base = sorted([x.c1 for x in cql.execute(f"SELECT c1 FROM {table}")])
|
|
list_view = sorted([x.c1 for x in cql.execute(f"SELECT c1 FROM {mv}")])
|
|
print("Remaining base rows: ", len(list_base))
|
|
print("Remaining base rows: ", len(list_view))
|
|
print("Only in base: ", sorted(list(set(list_base)-set(list_view))))
|
|
print("Only in view: ", sorted(list(set(list_view)-set(list_base))))
|
|
assert list_base == list_view
|
|
|
|
# Test that deleting a base partition works fine, even if it produces a
|
|
# large batch of individual view updates. After issue #8852 was fixed,
|
|
# this large batch is no longer done together, but rather split to smaller
|
|
# batches, and this split can be done wrongly (e.g., see issue #17117)
|
|
# and we want to confirm that all the deletions are actually done.
|
|
#
|
|
# We have the related test for secondary indexes (test_secondary_index.py::
|
|
# test_partition_deletion), but this one uses materialized views directly
|
|
# instead of the secondary-index wrapper, and works on Cassandra as well.
|
|
# This test also exercises a more difficult scenario, where all view
|
|
# deletions end up in the same view partition, so the code is "tempted" to
|
|
# keep them all in the same output mutation and needs to break up this
|
|
# output mutation correctly (the test doesn't check that this breaking up
|
|
# happens, but rather that if it happens - it doesn't break correctness).
|
|
def test_base_partition_deletion(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, v int, primary key (p,c)') as table:
|
|
# All inserts go to the same base partition, that we'll then delete
|
|
p = 1
|
|
v = 42
|
|
insert = cql.prepare(f'INSERT INTO {table} (p,c,v) VALUES ({p},?,{v})')
|
|
# Case where all view-row deletions go to the same view partition:
|
|
with new_materialized_view(cql, table, '*', 'p,v,c', 'p is not null and v is not null and c is not null') as mv:
|
|
N = 345
|
|
for i in range(N):
|
|
cql.execute(insert, [i])
|
|
# Before the deletion, all N rows should exist in the base and the
|
|
# view
|
|
allN = list(range(N))
|
|
assert allN == [x.c for x in cql.execute(f"SELECT c FROM {table}")]
|
|
assert allN == sorted([x.c for x in cql.execute(f"SELECT c FROM {mv}")])
|
|
cql.execute(f"DELETE FROM {table} WHERE p=1")
|
|
# After the deletion, all data should be gone from both base and view
|
|
assert [] == list(cql.execute(f"SELECT c FROM {table}"))
|
|
assert [] == list(cql.execute(f"SELECT c FROM {mv}"))
|
|
|
|
# Same as above test, just for a range tombstone, e.g., in a composite
|
|
# clustering key c1,c2 deleting in the base all rows with some c1.
|
|
# Here too Scylla generates a long list of view updates (individual row
|
|
# deletions), and if it's split into smaller batches, this needs to be
|
|
# done correctly and no view update missed.
|
|
# This test is related to issue #17117 - it doesn't reproduce that issue
|
|
# (we have reproducers for it above), but it's important to confirm that
|
|
# after fixing that issue, we don't break this case and can still split
|
|
# a large clustering prefix deletion into multiple batches without losing
|
|
# any view deletions.
|
|
def test_base_clustering_prefix_deletion(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c1 int, c2 int, v int, primary key (p,c1,c2)') as table:
|
|
# All inserts go to the same base c1, that we'll then delete
|
|
p = 1
|
|
c1 = 2
|
|
v = 42
|
|
insert = cql.prepare(f'INSERT INTO {table} (p,c1,c2,v) VALUES ({p},{c1},?,{v})')
|
|
# Case where all view-row deletions go to the same view partition:
|
|
with new_materialized_view(cql, table, '*', 'p,v,c1,c2', 'p is not null and v is not null and c1 is not null and c2 is not null') as mv:
|
|
N = 345
|
|
for i in range(N):
|
|
cql.execute(insert, [i])
|
|
# Before the deletion, all N rows should exist in the base and the
|
|
# view
|
|
allN = list(range(N))
|
|
assert allN == [x.c2 for x in cql.execute(f"SELECT c2 FROM {table}")]
|
|
assert allN == sorted([x.c2 for x in cql.execute(f"SELECT c2 FROM {mv}")])
|
|
cql.execute(f"DELETE FROM {table} WHERE p=1")
|
|
# After the deletion, all data should be gone from both base and view
|
|
assert [] == list(cql.execute(f"SELECT c2 FROM {table}"))
|
|
assert [] == list(cql.execute(f"SELECT c2 FROM {mv}"))
|
|
|
|
# Test deleting an entire base partition, where there is a view with the same or
|
|
# different partition key. When the view has the same partition key as base,
|
|
# the partition deletion can be done on the base in one update of partition
|
|
# tombstone. In other cases, a tombstone is generated for each row that
|
|
# corresponds to the deleted base partition.
|
|
def test_base_partition_deletion_with_same_view_partition_key(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, v int, primary key (p,c)') as table:
|
|
# Insert into two base partitions. We will delete one of them
|
|
v = 42
|
|
insert = cql.prepare(f'INSERT INTO {table} (p,c,v) VALUES (?,?,{v})')
|
|
# Create multiple views with different primary keys.
|
|
# The first view has the same partition key as the base, so the entire partition will be deleted on the view as well.
|
|
# The other views have different partition key than the base, so they will have individual rows removed.
|
|
with new_materialized_view(cql, table, '*', 'p,c', 'p is not null and c is not null') as mv1, \
|
|
new_materialized_view(cql, table, '*', 'c,p', 'p is not null and c is not null') as mv2, \
|
|
new_materialized_view(cql, table, '*', '(p,c),v', 'p is not null and c is not null and v is not null') as mv3:
|
|
N = 10
|
|
for i in range(N):
|
|
cql.execute(insert, [1, i])
|
|
cql.execute(insert, [2, i])
|
|
|
|
# Before the deletion, all N rows should exist in the base and the view
|
|
allN = list(range(N))
|
|
assert allN == [x.c for x in cql.execute(f"SELECT c FROM {table} WHERE p=1")]
|
|
assert allN == sorted([x.c for x in cql.execute(f"SELECT c FROM {mv1} WHERE p=1")])
|
|
assert allN == [x.c for x in cql.execute(f"SELECT c FROM {table} WHERE p=2")]
|
|
assert allN == sorted([x.c for x in cql.execute(f"SELECT c FROM {mv1} WHERE p=2")])
|
|
for i in range(N):
|
|
assert [1,2] == sorted([x.p for x in cql.execute(f"SELECT p FROM {mv2} WHERE c={i}")])
|
|
|
|
cql.execute(f"DELETE FROM {table} WHERE p=1")
|
|
|
|
# After the deletion, all data should be gone from both base and view
|
|
assert [] == list(cql.execute(f"SELECT c FROM {table} WHERE p=1"))
|
|
assert [] == list(cql.execute(f"SELECT c FROM {mv1} WHERE p=1"))
|
|
assert [] == list(cql.execute(f"SELECT c FROM {mv2} WHERE p=1 ALLOW FILTERING"))
|
|
assert [] == list(cql.execute(f"SELECT c FROM {mv3} WHERE p=1 ALLOW FILTERING"))
|
|
|
|
assert allN == [x.c for x in cql.execute(f"SELECT c FROM {table} WHERE p=2")]
|
|
assert allN == sorted([x.c for x in cql.execute(f"SELECT c FROM {mv1} WHERE p=2")])
|
|
|
|
for i in range(N):
|
|
assert [2] == sorted([x.p for x in cql.execute(f"SELECT p FROM {mv2} WHERE c={i}")])
|
|
|
|
for i in range(N):
|
|
assert [v] == sorted([x.v for x in cql.execute(f"SELECT v FROM {mv3} WHERE p=2 AND c={i}")])
|
|
|
|
# The partition key of the view is strictly contained in the base partition key,
|
|
# so multiple base partitions are combined into one view partition.
|
|
# Test deleting a base partition and verify it is deleted correctly in the view.
|
|
def test_base_partition_deletion_with_smaller_view_partition_key(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p1 int, p2 int, c int, primary key ((p1,p2),c)') as table:
|
|
insert = cql.prepare(f'INSERT INTO {table} (p1,p2,c) VALUES (?,?,?)')
|
|
with new_materialized_view(cql, table, '*', 'p1,p2,c', 'p1 is not null and p2 is not null and c is not null') as mv:
|
|
# Insert into two separate base partitions.
|
|
# In the view, the rows have the same partition key.
|
|
cql.execute(insert, [0, 0, 10])
|
|
cql.execute(insert, [0, 1, 20])
|
|
|
|
# Delete one of the partitions
|
|
cql.execute(f"DELETE FROM {table} WHERE p1=0 AND p2=0")
|
|
|
|
assert [] == list(cql.execute(f"SELECT c FROM {table} WHERE p1=0 AND p2=0"))
|
|
assert [20] == [x.c for x in cql.execute(f"SELECT c FROM {table} WHERE p1=0 AND p2=1")]
|
|
|
|
assert [(1,20)] == [(x.p2, x.c) for x in cql.execute(f"SELECT p2, c FROM {mv} WHERE p1=0")]
|
|
|
|
# Test deleting a large partition when there is a view with the same partition
|
|
# key, and verify that view updates metrics is increased by exactly 1. Deleting
|
|
# a partition in this case is expected to generate one view update for deleting
|
|
# the corresponding view partition by a partition tombstone.
|
|
# Reproduces #8199
|
|
@pytest.mark.parametrize("permuted", [False, True])
|
|
def test_base_partition_deletion_with_metrics(cql, test_keyspace, scylla_only, permuted):
|
|
with new_test_table(cql, test_keyspace, 'p1 int, p2 int, c int, primary key ((p1,p2),c)') as table:
|
|
# Insert into one base partition. We will delete the entire partition
|
|
insert = cql.prepare(f'INSERT INTO {table} (p1,p2,c) VALUES (?,?,?)')
|
|
# The view partition key is a permutation of the base partition key.
|
|
with new_materialized_view(cql, table, '*', '(p2,p1),c' if permuted else '(p1,p2),c', 'p1 is not null and p2 is not null and c is not null') as mv:
|
|
# the metric total_view_updates_pushed_local is incremented by 1 for each 100 row view
|
|
# updates, because it is collected in batches according to max_rows_for_view_updates.
|
|
# To verify the behavior, we want the metric to increase by at least 2 without the optimization,
|
|
# so 101 is the minimum value that works. With the optimization, we expect to have exactly 1 update
|
|
# for any N.
|
|
N = 101
|
|
|
|
# all operations are on this single partition
|
|
p1, p2 = 1, 10
|
|
where_clause_table = f"WHERE p1={p1} AND p2={p2}"
|
|
where_clause_mv = f"WHERE p2={p2} AND p1={p1}" if permuted else where_clause_table
|
|
|
|
for i in range(N):
|
|
cql.execute(insert, [p1, p2, i])
|
|
|
|
# Before the deletion, all N rows should exist in the base and the view
|
|
allN = list(range(N))
|
|
assert allN == [x.c for x in cql.execute(f"SELECT c FROM {table} {where_clause_table}")]
|
|
assert allN == sorted([x.c for x in cql.execute(f"SELECT c FROM {mv} {where_clause_mv}")])
|
|
|
|
metrics_before = ScyllaMetrics.query(cql)
|
|
updates_before = metrics_before.get('scylla_database_total_view_updates_pushed_local')
|
|
|
|
cql.execute(f"DELETE FROM {table} {where_clause_table}")
|
|
|
|
# After the deletion, all data should be gone from both base and view
|
|
assert [] == list(cql.execute(f"SELECT c FROM {table} {where_clause_table}"))
|
|
assert [] == list(cql.execute(f"SELECT c FROM {mv} {where_clause_mv}"))
|
|
|
|
metrics_after = ScyllaMetrics.query(cql)
|
|
updates_after = metrics_after.get('scylla_database_total_view_updates_pushed_local')
|
|
|
|
print(f"scylla_database_total_view_updates_pushed_local: {updates_before} -> {updates_after}")
|
|
assert updates_after == updates_before + 1
|
|
|
|
# Perform a batch operation, deleting a partition and also inserting a row
|
|
# to that partition with a newer timestamp, and verify that the insertion
|
|
# is not lost in the MV update.
|
|
def test_base_partition_deletion_in_batch_with_insert(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, primary key (p,c)') as table:
|
|
insert = cql.prepare(f'INSERT INTO {table} (p,c) VALUES (?,?) USING TIMESTAMP 99')
|
|
with new_materialized_view(cql, table, '*', 'p,c', 'p is not null and c is not null') as mv:
|
|
cql.execute(insert, [0, 1])
|
|
cql.execute(insert, [0, 2])
|
|
cql.execute(insert, [0, 3])
|
|
|
|
# This should delete all the existing partition rows, and the new
|
|
# row insertion survives and remains the only row after the operation
|
|
# since it has the most recent timestamp.
|
|
cmd = 'BEGIN UNLOGGED BATCH '
|
|
cmd += f'INSERT INTO {table} (p,c) VALUES (0,4) USING TIMESTAMP 98; '
|
|
cmd += f'DELETE FROM {table} USING TIMESTAMP 100 WHERE p=0; '
|
|
cmd += f'INSERT INTO {table} (p,c) VALUES (0,5) USING TIMESTAMP 101; '
|
|
cmd += 'APPLY BATCH;'
|
|
cql.execute(cmd)
|
|
|
|
# Verify it is correct both in the table and the view
|
|
assert [5] == [x.c for x in cql.execute(f"SELECT c FROM {table} WHERE p=0")]
|
|
assert [5] == [x.c for x in cql.execute(f"SELECT c FROM {mv} WHERE p=0")]
|
|
|
|
# Similar to the test above, perform a deletion of a base partition in a batch with
|
|
# deletion of individual rows. Verify the partition is deleted correctly and that
|
|
# a single update is generated for the view for deleting the whole partition, and no
|
|
# view updates for each row.
|
|
def test_base_partition_deletion_in_batch_with_delete_row_with_metrics(cql, test_keyspace, scylla_only):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, v int, primary key ((p,c),v)') as table:
|
|
insert = cql.prepare(f'INSERT INTO {table} (p,c,v) VALUES (?,?,?)')
|
|
# The view partition key is the same as the base partition key.
|
|
with new_materialized_view(cql, table, '*', '(p,c),v', 'p is not null and c is not null and v is not null') as mv:
|
|
N = 101 # See comment above
|
|
for i in range(N):
|
|
cql.execute(insert, [1, 10, i])
|
|
|
|
# Before the deletion, all N rows should exist in the base and the view
|
|
allN = list(range(N))
|
|
assert allN == [x.v for x in cql.execute(f"SELECT v FROM {table} WHERE p=1 AND c=10")]
|
|
assert allN == sorted([x.v for x in cql.execute(f"SELECT v FROM {mv} WHERE p=1 AND c=10")])
|
|
|
|
metrics_before = ScyllaMetrics.query(cql)
|
|
updates_before = metrics_before.get('scylla_database_total_view_updates_pushed_local')
|
|
|
|
# The batch deletes the entire partition and also, redundantly, deleting individual rows in the partition.
|
|
# We expect the view update to contain only a single update for deleting the partition.
|
|
cmd = 'BEGIN UNLOGGED BATCH '
|
|
for i in range(100,500):
|
|
cmd += f'DELETE FROM {table} WHERE p=1 AND c=10 AND v={i}; '
|
|
cmd += f'DELETE FROM {table} WHERE p=1 AND c=10; '
|
|
cmd += 'APPLY BATCH;'
|
|
cql.execute(cmd)
|
|
|
|
# Verify the partition is deleted
|
|
assert [] == list(cql.execute(f"SELECT v FROM {table} WHERE p=1 AND c=10"))
|
|
assert [] == list(cql.execute(f"SELECT v FROM {mv} WHERE p=1 AND c=10"))
|
|
|
|
# Verify there is a single view update
|
|
metrics_after = ScyllaMetrics.query(cql)
|
|
updates_after = metrics_after.get('scylla_database_total_view_updates_pushed_local')
|
|
|
|
print(f"scylla_database_total_view_updates_pushed_local: {updates_before} -> {updates_after}")
|
|
assert updates_after == updates_before + 1
|
|
|
|
# Delete a base partition using a timestamp lower than some of the rows
|
|
# in the partition. Verify it doesn't result new delete in the base
|
|
# and the view partition.
|
|
def test_base_partition_deletion_with_low_timestamp(cql, test_keyspace):
|
|
with new_test_table(cql, test_keyspace, 'p int, c int, primary key (p,c)') as table:
|
|
with new_materialized_view(cql, table, '*', 'p,c', 'p is not null and c is not null') as mv:
|
|
cql.execute(f'INSERT INTO {table} (p,c) VALUES (0,1) USING TIMESTAMP 99')
|
|
cql.execute(f'INSERT INTO {table} (p,c) VALUES (0,2) USING TIMESTAMP 101')
|
|
|
|
# Delete the partition with a timestamp which is older than some of
|
|
# the rows and newer than other rows.
|
|
cql.execute(f'DELETE FROM {table} USING TIMESTAMP 100 WHERE p=0')
|
|
|
|
# Verify we get only the row with the newer timestamp
|
|
assert [2] == [x.c for x in cql.execute(f"SELECT c FROM {table} WHERE p=0")]
|
|
assert [2] == [x.c for x in cql.execute(f"SELECT c FROM {mv} WHERE p=0")]
|