# Copyright 2019-present ScyllaDB # # SPDX-License-Identifier: LicenseRef-ScyllaDB-Source-Available-1.0 # Tests of LSI (Local Secondary Indexes) # # Note that many of these tests are slower than usual, because many of them # need to create new tables and/or new LSIs of different types, operations # which are extremely slow in DynamoDB, often taking minutes (!). import time import pytest import requests from botocore.exceptions import ClientError from test.alternator.util import create_test_table, new_test_table, random_string, full_scan, full_query, multiset, unique_table_name # LSIs support strongly-consistent reads, so the following functions do not # need to retry like we did in test_gsi.py for GSIs: def assert_index_query(table, index_name, expected_items, **kwargs): assert multiset(expected_items) == multiset(full_query(table, IndexName=index_name, **kwargs)) def assert_index_scan(table, index_name, expected_items, **kwargs): assert multiset(expected_items) == multiset(full_scan(table, IndexName=index_name, **kwargs)) # A version doing retries instead of ConsistentRead, to be used just for the # one test below which has both GSI and LSI: def retrying_assert_index_query(table, index_name, expected_items, **kwargs): for i in range(3): if multiset(expected_items) == multiset(full_query(table, IndexName=index_name, ConsistentRead=False, **kwargs)): return print('retrying_assert_index_query retrying') time.sleep(1) assert multiset(expected_items) == multiset(full_query(table, IndexName=index_name, ConsistentRead=False, **kwargs)) # Although quite silly, it is actually allowed to create an index which is # identical to the base table. def test_lsi_identical(dynamodb): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' }], AttributeDefinitions=[{ 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [{ 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' }], 'Projection': { 'ProjectionType': 'ALL' } } ]) items = [{'p': random_string(), 'c': random_string()} for i in range(10)] with table.batch_writer() as batch: for item in items: batch.put_item(item) # Scanning the entire table directly or via the index yields the same # results (in different order). assert multiset(items) == multiset(full_scan(table)) assert_index_scan(table, 'hello', items) # We can't scan a non-existent index with pytest.raises(ClientError, match='ValidationException'): full_scan(table, IndexName='wrong') table.delete() # Check that providing a hash key different than the base table is not # allowed: def test_lsi_wrong_different_hash(dynamodb): with pytest.raises(ClientError, match='ValidationException.*hash key'): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' }], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'b', 'AttributeType': 'S' } ], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [ { 'AttributeName': 'b', 'KeyType': 'HASH' }, { 'AttributeName': 'p', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'ALL' } } ]) table.delete() # Check that it's not allowed to create an LSI without specifying a range # key cannot be missing, or (obviously) making it the same as the hash key: def test_lsi_wrong_bad_range(dynamodb): with pytest.raises(ClientError, match='ValidationException.*same'): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' } ], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'p', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'ALL' } } ]) table.delete() with pytest.raises(ClientError, match='ValidationException.*'): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, ], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' } ], 'Projection': { 'ProjectionType': 'ALL' } } ]) table.delete() # The purpose of an LSI is to allow an alternative sort key for the # existing partitions - the partitions do not change. So it doesn't make # sense to create an LSI on a table that did not originally have a sort key # (so has only single-item partitions) - and this case is not allowed. def test_lsi_wrong_no_sort_key(dynamodb): with pytest.raises(ClientError, match='ValidationException.*'): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, ], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'ALL' } } ]) table.delete() # A simple scenario for LSI. Base table has a partition key and a sort key, # index has the same partition key key but a different sort key - one of # the non-key attributes from the base table. @pytest.fixture(scope="module") def test_table_lsi_1(dynamodb): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'b', 'AttributeType': 'S' }, ], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'b', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'ALL' } } ]) yield table table.delete() def test_lsi_1(test_table_lsi_1): items1 = [{'p': random_string(), 'c': random_string(), 'b': random_string()} for i in range(10)] p1, b1 = items1[0]['p'], items1[0]['b'] p2, b2 = random_string(), random_string() items2 = [{'p': p2, 'c': p2, 'b': b2}] items = items1 + items2 with test_table_lsi_1.batch_writer() as batch: for item in items: batch.put_item(item) expected_items = [i for i in items if i['p'] == p1 and i['b'] == b1] assert_index_query(test_table_lsi_1, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p1], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b1], 'ComparisonOperator': 'EQ'}}) expected_items = [i for i in items if i['p'] == p2 and i['b'] == b2] assert_index_query(test_table_lsi_1, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p2], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b2], 'ComparisonOperator': 'EQ'}}) # The same as test_table_lsi_1, but with a clustering key of type bytes @pytest.fixture(scope="module") def test_table_lsi_2(dynamodb): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'b', 'AttributeType': 'B' }, ], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'b', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'ALL' } } ]) yield table table.delete() # A second scenario of LSI. Base table has both hash and sort keys, # a local index is created on each non-key parameter @pytest.fixture(scope="module") def test_table_lsi_4(dynamodb): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'x1', 'AttributeType': 'S' }, { 'AttributeName': 'x2', 'AttributeType': 'S' }, { 'AttributeName': 'x3', 'AttributeType': 'S' }, { 'AttributeName': 'x4', 'AttributeType': 'S' }, ], LocalSecondaryIndexes=[ { 'IndexName': 'hello_' + column, 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': column, 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'ALL' } } for column in ['x1','x2','x3','x4'] ]) yield table table.delete() def test_lsi_4(test_table_lsi_4): items1 = [{'p': random_string(), 'c': random_string(), 'x1': random_string(), 'x2': random_string(), 'x3': random_string(), 'x4': random_string()} for i in range(10)] i_values = items1[0] i5 = random_string() items2 = [{'p': i5, 'c': i5, 'x1': i5, 'x2': i5, 'x3': i5, 'x4': i5}] items = items1 + items2 with test_table_lsi_4.batch_writer() as batch: for item in items: batch.put_item(item) for column in ['x1', 'x2', 'x3', 'x4']: expected_items = [i for i in items if (i['p'], i[column]) == (i_values['p'], i_values[column])] assert_index_query(test_table_lsi_4, 'hello_' + column, expected_items, KeyConditions={'p': {'AttributeValueList': [i_values['p']], 'ComparisonOperator': 'EQ'}, column: {'AttributeValueList': [i_values[column]], 'ComparisonOperator': 'EQ'}}) expected_items = [i for i in items if (i['p'], i[column]) == (i5, i5)] assert_index_query(test_table_lsi_4, 'hello_' + column, expected_items, KeyConditions={'p': {'AttributeValueList': [i5], 'ComparisonOperator': 'EQ'}, column: {'AttributeValueList': [i5], 'ComparisonOperator': 'EQ'}}) # Test that setting an indexed string column to an empty string is illegal, # since keys cannot contain empty strings def test_lsi_empty_value(test_table_lsi_1): with pytest.raises(ClientError, match='ValidationException.*empty'): test_table_lsi_1.put_item(Item={'p': random_string(), 'c': random_string(), 'b': ''}) # Setting a binary key to an empty value is also illegal. def test_lsi_empty_value_binary(test_table_lsi_2): with pytest.raises(ClientError, match='ValidationException.*empty'): test_table_lsi_2.put_item(Item={'p': random_string(), 'c': random_string(), 'b': b''}) # Test that if an item in a batch has an empty indexed column and fails the # verification, none of the other writes in the batch get done either. def test_lsi_empty_value_in_bigger_batch_write(test_table_lsi_1): items = [ {'p': random_string(), 'c': random_string(), 'b': random_string()}, {'p': random_string(), 'c': random_string(), 'b': random_string()}, {'p': random_string(), 'c': random_string(), 'b': ''} ] with pytest.raises(ClientError, match='ValidationException.*empty'): with test_table_lsi_1.batch_writer() as batch: for item in items: batch.put_item(item) for item in items: assert not 'Item' in test_table_lsi_1.get_item(Key={'p': item['p'], 'c': item['c']}, ConsistentRead=True) def test_lsi_null_index(test_table_lsi_1): # Dynamodb supports special way of setting NULL value. It's different than # non existing value. p = random_string() c = random_string() with pytest.raises(ClientError, match='ValidationException.*NULL'): test_table_lsi_1.put_item(Item={'p': p, 'c': c, 'b': None}) with pytest.raises(ClientError, match='ValidationException.*NULL'): test_table_lsi_1.update_item(Key={'p': p, 'c': c}, AttributeUpdates={'b': {'Value': None, 'Action': 'PUT'}}) with pytest.raises(ClientError, match='ValidationException.*NULL'): with test_table_lsi_1.batch_writer() as batch: batch.put_item({'p': p, 'c': c, 'b': None}) def test_lsi_describe(test_table_lsi_4): desc = test_table_lsi_4.meta.client.describe_table(TableName=test_table_lsi_4.name) assert 'Table' in desc assert 'LocalSecondaryIndexes' in desc['Table'] lsis = desc['Table']['LocalSecondaryIndexes'] assert(sorted([lsi['IndexName'] for lsi in lsis]) == ['hello_x1', 'hello_x2', 'hello_x3', 'hello_x4']) for lsi in lsis: assert lsi['IndexArn'] == desc['Table']['TableArn'] + '/index/' + lsi['IndexName'] assert lsi['Projection'] == {'ProjectionType': 'ALL'} # Whereas GSIs have an IndexStatus when described by DescribeTable, # LSIs do not. IndexStatus is not needed because LSIs cannot be added # after the base table is created. def test_lsi_describe_indexstatus(test_table_lsi_1): desc = test_table_lsi_1.meta.client.describe_table(TableName=test_table_lsi_1.name) assert 'Table' in desc assert 'LocalSecondaryIndexes' in desc['Table'] lsis = desc['Table']['LocalSecondaryIndexes'] assert len(lsis) == 1 lsi = lsis[0] assert not 'IndexStatus' in lsi # In addition to the basic listing of an LSI in DescribeTable tested above, # in this test we check additional fields that should appear in each LSI's # description. @pytest.mark.xfail(reason="issues #7550, #11466") def test_lsi_describe_fields(test_table_lsi_1): desc = test_table_lsi_1.meta.client.describe_table(TableName=test_table_lsi_1.name) assert 'Table' in desc assert 'LocalSecondaryIndexes' in desc['Table'] lsis = desc['Table']['LocalSecondaryIndexes'] assert len(lsis) == 1 lsi = lsis[0] assert lsi['IndexName'] == 'hello' assert 'IndexSizeBytes' in lsi # actual size depends on content assert 'ItemCount' in lsi # Whereas GSIs has ProvisionedThroughput, LSIs do not. An LSI shares # its provisioning with the base table. assert not 'ProvisionedThroughput' in lsi assert lsi['KeySchema'] == [{'KeyType': 'HASH', 'AttributeName': 'p'}, {'KeyType': 'RANGE', 'AttributeName': 'b'}] # The index's ARN should look like the table's ARN followed by /index/. assert lsi['IndexArn'] == desc['Table']['TableArn'] + '/index/hello' # A table with selective projection - only keys are projected into the index @pytest.fixture(scope="module") def test_table_lsi_keys_only(dynamodb): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'b', 'AttributeType': 'S' } ], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'b', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'KEYS_ONLY' } } ]) yield table table.delete() # Check that it's possible to extract a non-projected attribute from the index, # as the documentation promises def test_lsi_get_not_projected_attribute(test_table_lsi_keys_only): items1 = [{'p': random_string(), 'c': random_string(), 'b': random_string(), 'd': random_string()} for i in range(10)] p1, b1, d1 = items1[0]['p'], items1[0]['b'], items1[0]['d'] p2, b2, d2 = random_string(), random_string(), random_string() items2 = [{'p': p2, 'c': p2, 'b': b2, 'd': d2}] items = items1 + items2 with test_table_lsi_keys_only.batch_writer() as batch: for item in items: batch.put_item(item) expected_items = [i for i in items if i['p'] == p1 and i['b'] == b1 and i['d'] == d1] assert_index_query(test_table_lsi_keys_only, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p1], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b1], 'ComparisonOperator': 'EQ'}}, Select='ALL_ATTRIBUTES') expected_items = [i for i in items if i['p'] == p2 and i['b'] == b2 and i['d'] == d2] assert_index_query(test_table_lsi_keys_only, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p2], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b2], 'ComparisonOperator': 'EQ'}}, Select='ALL_ATTRIBUTES') expected_items = [{'d': i['d']} for i in items if i['p'] == p2 and i['b'] == b2 and i['d'] == d2] assert_index_query(test_table_lsi_keys_only, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p2], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b2], 'ComparisonOperator': 'EQ'}}, Select='SPECIFIC_ATTRIBUTES', AttributesToGet=['d']) # Check that by default (Select=ALL_PROJECTED_ATTRIBUTES), only projected # attributes are extracted @pytest.mark.xfail(reason="LSI in alternator currently only implement full projections") def test_lsi_get_all_projected_attributes(test_table_lsi_keys_only): items1 = [{'p': random_string(), 'c': random_string(), 'b': random_string(), 'd': random_string()} for i in range(10)] p1, b1, d1 = items1[0]['p'], items1[0]['b'], items1[0]['d'] p2, b2, d2 = random_string(), random_string(), random_string() items2 = [{'p': p2, 'c': p2, 'b': b2, 'd': d2}] items = items1 + items2 with test_table_lsi_keys_only.batch_writer() as batch: for item in items: batch.put_item(item) expected_items = [{'p': i['p'], 'c': i['c'],'b': i['b']} for i in items if i['p'] == p1 and i['b'] == b1] assert_index_query(test_table_lsi_keys_only, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p1], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b1], 'ComparisonOperator': 'EQ'}}) # Test the "Select" parameter of a Query on a LSI. We have in test_query.py # a test 'test_query_select' for this parameter on a query of a normal (base) # table, but for GSI and LSI the ALL_PROJECTED_ATTRIBUTES is additionally # allowed (and in fact is the default), and we want to test it. @pytest.mark.xfail(reason="Projection and Select not supported yet. Issue #5036, #5058") def test_lsi_query_select(dynamodb): with new_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'b', 'AttributeType': 'S' }, ], LocalSecondaryIndexes=[ { 'IndexName': 'hello', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'b', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'INCLUDE', 'NonKeyAttributes': ['a'] } } ]) as table: items = [{'p': random_string(), 'c': random_string(), 'b': random_string(), 'a': random_string(), 'x': random_string()} for i in range(10)] with table.batch_writer() as batch: for item in items: batch.put_item(item) p = items[0]['p'] b = items[0]['b'] # Although in LSI all attributes are available (as we'll check # below) the default Select is ALL_PROJECTED_ATTRIBUTES, and # returns just the projected attributes (in this case all key # attributes in either base or LSI, and 'a' - but not 'x'): expected_items = [{'p': z['p'], 'c': z['c'], 'b': z['b'], 'a': z['a']} for z in items if z['b'] == b] assert_index_query(table, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b], 'ComparisonOperator': 'EQ'}}) assert_index_query(table, 'hello', expected_items, Select='ALL_PROJECTED_ATTRIBUTES', KeyConditions={'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b], 'ComparisonOperator': 'EQ'}}) # Unlike in GSI, in LSI Select=ALL_ATTRIBUTES *is* allowed even # when only a subset of the attributes being projected: expected_items = [z for z in items if z['b'] == b] assert_index_query(table, 'hello', expected_items, Select='ALL_ATTRIBUTES', KeyConditions={'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b], 'ComparisonOperator': 'EQ'}}) # Also in LSI, SPECIFIC_ATTRIBUTES (with AttributesToGet / # ProjectionExpression) is allowed for any attribute, projected # or not projected. Let's try 'a' (projected) and 'x' (not projected): expected_items = [{'a': z['a'], 'x': z['x']} for z in items if z['b'] == b] assert_index_query(table, 'hello', expected_items, Select='SPECIFIC_ATTRIBUTES', AttributesToGet=['a', 'x'], KeyConditions={'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b], 'ComparisonOperator': 'EQ'}}) # Select=COUNT is also allowed, and as expected returns no content. assert not 'Items' in table.query(ConsistentRead=False, IndexName='hello', Select='COUNT', KeyConditions={'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b], 'ComparisonOperator': 'EQ'}}) # Check that strongly consistent reads are allowed for LSI def test_lsi_consistent_read(test_table_lsi_1): items1 = [{'p': random_string(), 'c': random_string(), 'b': random_string()} for i in range(10)] p1, b1 = items1[0]['p'], items1[0]['b'] p2, b2 = random_string(), random_string() items2 = [{'p': p2, 'c': p2, 'b': b2}] items = items1 + items2 with test_table_lsi_1.batch_writer() as batch: for item in items: batch.put_item(item) expected_items = [i for i in items if i['p'] == p1 and i['b'] == b1] assert_index_query(test_table_lsi_1, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p1], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b1], 'ComparisonOperator': 'EQ'}}) expected_items = [i for i in items if i['p'] == p2 and i['b'] == b2] assert_index_query(test_table_lsi_1, 'hello', expected_items, KeyConditions={'p': {'AttributeValueList': [p2], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b2], 'ComparisonOperator': 'EQ'}}) # A table with both gsi and lsi present @pytest.fixture(scope="module") def test_table_lsi_gsi(dynamodb): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'x1', 'AttributeType': 'S' }, ], GlobalSecondaryIndexes=[ { 'IndexName': 'hello_g1', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'x1', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'KEYS_ONLY' } } ], LocalSecondaryIndexes=[ { 'IndexName': 'hello_l1', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'x1', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'KEYS_ONLY' } } ]) yield table table.delete() # Test that GSI and LSI can coexist, even if they're identical def test_lsi_and_gsi(test_table_lsi_gsi): desc = test_table_lsi_gsi.meta.client.describe_table(TableName=test_table_lsi_gsi.name) assert 'Table' in desc assert 'LocalSecondaryIndexes' in desc['Table'] assert 'GlobalSecondaryIndexes' in desc['Table'] lsis = desc['Table']['LocalSecondaryIndexes'] gsis = desc['Table']['GlobalSecondaryIndexes'] assert(sorted([lsi['IndexName'] for lsi in lsis]) == ['hello_l1']) assert(sorted([gsi['IndexName'] for gsi in gsis]) == ['hello_g1']) items = [{'p': random_string(), 'c': random_string(), 'x1': random_string()} for i in range(17)] p1, x1 = items[0]['p'], items[0]['x1'] with test_table_lsi_gsi.batch_writer() as batch: for item in items: batch.put_item(item) for index in ['hello_g1', 'hello_l1']: expected_items = [i for i in items if i['p'] == p1 and i['x1'] == x1] retrying_assert_index_query(test_table_lsi_gsi, index, expected_items, KeyConditions={'p': {'AttributeValueList': [p1], 'ComparisonOperator': 'EQ'}, 'x1': {'AttributeValueList': [x1], 'ComparisonOperator': 'EQ'}}) # This test is a version of test_filter_expression_and_projection_expression # from test_filter_expression, which involves a Query which projects only # one column but filters on another one, and the point is to verify that # the implementation got also the filtered column (for the filtering to work) # but did not return it with the results. This version does the same, except # that either the filtered column, or the projected column, is an LSI key. # In our implementation, LSI keys are implemented differently from ordinary # attributes - they are real Scylla columns and not just items in the # ":attrs" map - so this test checks that our implementation of the filtering # and projection (and their combination) did not mess up this special case. # This test reproduces issue #6951. def test_lsi_filter_expression_and_projection_expression(test_table_lsi_1): p = random_string() test_table_lsi_1.put_item(Item={'p': p, 'c': 'hi', 'b': 'dog', 'y': 'cat'}) test_table_lsi_1.put_item(Item={'p': p, 'c': 'yo', 'b': 'mouse', 'y': 'horse'}) # Case 1: b (the LSI key) is in filter but not in projection: got_items = full_query(test_table_lsi_1, KeyConditionExpression='p=:p', FilterExpression='b=:b', ProjectionExpression='y', ExpressionAttributeValues={':p': p, ':b': 'mouse'}) assert(got_items == [{'y': 'horse'}]) # Case 2: b (the LSI key) is in the projection, but not the filter: got_items = full_query(test_table_lsi_1, KeyConditionExpression='p=:p', FilterExpression='y=:y', ProjectionExpression='b', ExpressionAttributeValues={':p': p, ':y': 'cat'}) assert(got_items == [{'b': 'dog'}]) # We tested above that a table can have both an LSI and a GSI. # Although Alternator makes a distinction in how it stores the two types of # indexes, they cannot have the same name - because if they are created with # the same name, only one will be usable (the index is chosen via the # IndexName request attribute, which doesn't say if it's an LSI or GSI). # DynamoDB reports: "One or more parameter values were invalid: # Duplicate index name: samename" # Reproduces issue #10789. def test_lsi_and_gsi_same_name(dynamodb): with pytest.raises(ClientError, match='ValidationException.*Duplicate'): table = create_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' } ], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'x1', 'AttributeType': 'S' }, ], GlobalSecondaryIndexes=[ { 'IndexName': 'samename', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'x1', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'KEYS_ONLY' } } ], LocalSecondaryIndexes=[ { 'IndexName': 'samename', 'KeySchema': [ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'x1', 'KeyType': 'RANGE' } ], 'Projection': { 'ProjectionType': 'KEYS_ONLY' } } ]) table.delete() # Test that creating multiple LSIs with the same key schema but different names # is allowed. def test_lsi_identical_indexes_with_different_names(dynamodb): with new_test_table(dynamodb, KeySchema=[{ 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' }], AttributeDefinitions=[ { 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }, { 'AttributeName': 'x', 'AttributeType': 'S' }, ], LocalSecondaryIndexes=[ { 'IndexName': 'index1', 'KeySchema': [{ 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'x', 'KeyType': 'RANGE' }], 'Projection': { 'ProjectionType': 'ALL' } }, { 'IndexName': 'index2', 'KeySchema': [{ 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'x', 'KeyType': 'RANGE' }], 'Projection': { 'ProjectionType': 'ALL' } } ]): pass # Test that the LSI table can be addressed in Scylla's REST API (obviously, # since this test is for the REST API, it is Scylla-only and can't be run on # DynamoDB). # At the time this test was written, the LSI's name has a "!" in it, so this # test reproduces a bug in URL decoding (#5883). But the goal of this test # isn't to insist that a table backing an LSI must have a specific name, # but rather that whatever name it does have - it can be addressed. def test_lsi_name_rest_api(test_table_lsi_1, rest_api): # See that the LSI is listed in list of tables. It will be a table # whose CQL name contains the Alternator table's name, and the # LSI's name ('hello'). As of this writing, it will actually be # alternator_:!: - but the test doesn't enshrine this. resp = requests.get(f'{rest_api}/column_family/name') resp.raise_for_status() lsi_rest_name = None for name in resp.json(): if test_table_lsi_1.name in name and 'hello' in name: lsi_rest_name = name break assert lsi_rest_name # Attempt to run a request on this LSI's table name "lsi_rest_name". # We'll use the compaction_strategy request here, but if for some # reason in the future we decide to drop that request, any other # request will be fine. resp = requests.get(f'{rest_api}/column_family/compaction_strategy/{lsi_rest_name}') resp.raise_for_status() # Let's make things difficult for the server by URL encoding the # lsi_rest_name - exposing issue #5883. encoded_lsi_rest_name = requests.utils.quote(lsi_rest_name) resp = requests.get(f'{rest_api}/column_family/compaction_strategy/{encoded_lsi_rest_name}') resp.raise_for_status() # Test that when a table has an LSI, then if the indexed attribute is # missing, the item is added to the base table but not the index. def test_lsi_missing_attribute(test_table_lsi_1): p1 = random_string() c1 = random_string() b1 = random_string() p2 = random_string() c2 = random_string() test_table_lsi_1.put_item(Item={'p': p1, 'c': c1, 'b': b1}) test_table_lsi_1.put_item(Item={'p': p2, 'c': c2}) # missing b # Both items are now in the base table: assert test_table_lsi_1.get_item(Key={'p': p1, 'c': c1}, ConsistentRead=True)['Item'] == {'p': p1, 'c': c1, 'b': b1} assert test_table_lsi_1.get_item(Key={'p': p2, 'c': c2}, ConsistentRead=True)['Item'] == {'p': p2, 'c': c2} # But only the first item is in the index: The first item can be found # using a Query, and a scan of the index won't find the second item. # Note: with eventually consistent read, we can't really be sure that # the second item will "never" appear in the index. We do that read last, # so if we had a bug and such item did appear, hopefully we had enough # time for the bug to become visible. At least sometimes. assert_index_query(test_table_lsi_1, 'hello', [{'p': p1, 'c': c1, 'b': b1}], KeyConditions={ 'p': {'AttributeValueList': [p1], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b1], 'ComparisonOperator': 'EQ'}, }) assert not any([i['p'] == p2 and i['c'] == c2 for i in full_scan(test_table_lsi_1, ConsistentRead=False, IndexName='hello')]) # The wrong type attributes tests check if a table with an LSI on a string # attribute rejects operations setting the attribute to values of other type. def test_lsi_wrong_type_attribute_put(test_table_lsi_1): # PutItem with wrong type for 'b' is rejected, item isn't created even # in the base table. p = random_string() c = random_string() with pytest.raises(ClientError, match='ValidationException.*mismatch'): test_table_lsi_1.put_item(Item={'p': p, 'c': c, 'b': 3}) assert not 'Item' in test_table_lsi_1.get_item(Key={'p': p, 'c': c}, ConsistentRead=True) def test_lsi_wrong_type_attribute_update(test_table_lsi_1): # An UpdateItem with wrong type for 'b' is also rejected, but naturally # if the item already existed, it remains as it was. p = random_string() c = random_string() b = random_string() test_table_lsi_1.put_item(Item={'p': p, 'c': c, 'b': b}) with pytest.raises(ClientError, match='ValidationException.*mismatch'): test_table_lsi_1.update_item(Key={'p': p, 'c': c}, AttributeUpdates={'b': {'Value': 3, 'Action': 'PUT'}}) assert test_table_lsi_1.get_item(Key={'p': p, 'c': c}, ConsistentRead=True)['Item'] == {'p': p, 'c': c, 'b': b} # Since an LSI key b cannot be a map or an array, in particular updates to # nested attributes like b.y or b[1] are not legal. def test_lsi_wrong_type_attribute_update_nested(test_table_lsi_1): p = random_string() c = random_string() b = random_string() test_table_lsi_1.put_item(Item={'p': p, 'c': c, 'b': b}) # Here we try to write a map into the LSI key column b. with pytest.raises(ClientError, match='ValidationException.*mismatch'): test_table_lsi_1.update_item(Key={'p': p, 'c': c}, UpdateExpression='SET b = :val1', ExpressionAttributeValues={':val1': {'a': 3, 'b': 4}}) # Here we try to set b.y for the LSI key column b. Here DynamoDB and # Alternator produce different error messages - but both make sense. # DynamoDB says "Key attributes must be scalars; list random access '[]' # and map # lookup '.' are not allowed: IndexKey: b", while Alternator # complains that "document paths not valid for this item: b.y". with pytest.raises(ClientError, match='ValidationException'): test_table_lsi_1.update_item(Key={'p': p, 'c': c}, UpdateExpression='SET b.y = :val1', ExpressionAttributeValues={':val1': 3}) def test_lsi_wrong_type_attribute_batchwrite(test_table_lsi_1): # BatchWriteItem with wrong type for 'b' is rejected, item isn't created # even in the base table. p = random_string() c = random_string() with pytest.raises(ClientError, match='ValidationException.*mismatch'): with test_table_lsi_1.batch_writer() as batch: batch.put_item({'p': p, 'c': c, 'b': 3}) assert not 'Item' in test_table_lsi_1.get_item(Key={'p': p, 'c': c}, ConsistentRead=True) def test_lsi_wrong_type_attribute_batch(test_table_lsi_1): # In a BatchWriteItem, if any update is forbidden, the entire batch is # rejected, and none of the updates happen at all. p = [random_string() for _ in range(3)] c = [random_string() for _ in range(3)] items = [{'p': p[0], 'c': c[0], 'b': random_string()}, {'p': p[1], 'c': c[0], 'b': 3}, {'p': p[2], 'c': c[0], 'b': random_string()}] with pytest.raises(ClientError, match='ValidationException.*mismatch'): with test_table_lsi_1.batch_writer() as batch: for item in items: batch.put_item(item) for p, c in zip(p, c): assert not 'Item' in test_table_lsi_1.get_item(Key={'p': p, 'c': c}, ConsistentRead=True) # Utility function for creating a new table (whose name is chosen by # unique_table_name()) with an LSI with the given name. If creation was # successful, the table is deleted. Useful for testing which LSI names work. def create_lsi(dynamodb, index_name): with new_test_table(dynamodb, KeySchema=[ { 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' }], AttributeDefinitions=[{ 'AttributeName': 'p', 'AttributeType': 'S' }, { 'AttributeName': 'c', 'AttributeType': 'S' }], LocalSecondaryIndexes=[ { 'IndexName': index_name, 'KeySchema': [{ 'AttributeName': 'p', 'KeyType': 'HASH' }, { 'AttributeName': 'c', 'KeyType': 'RANGE' }], 'Projection': { 'ProjectionType': 'ALL' } } ]) as table: # Verify that the LSI wasn't just ignored assert 'LocalSecondaryIndexes' in table.meta.client.describe_table(TableName=table.name)['Table'] # Index names with 255 characters are allowed in Dynamo. In Scylla, the # limit is different - the sum of both table and index length plus an extra 2 # cannot exceed 222 characters. # (compare test_create_and_delete_table_255/222() and test_gsi_very_long_name*). @pytest.mark.xfail(reason="Alternator limits table name length + LSI name length to 220") def test_lsi_very_long_name_255(dynamodb): create_lsi(dynamodb, 'n' * 255) def test_lsi_very_long_name_256(dynamodb): with pytest.raises(ClientError, match='ValidationException'): create_lsi(dynamodb, 'n' * 256) def test_lsi_very_long_name_222(dynamodb, scylla_only): # If we subtract from 222 the table's name length (we assume that # unique_table_name() always returns the same length) and an extra 2, # this is how long the LSI's name may be: max = 222 - len(unique_table_name()) - 2 # This max length should work: create_lsi(dynamodb, 'n' * max) # But a name one byte longer should fail: with pytest.raises(ClientError, match='ValidationException.*total length'): create_lsi(dynamodb, 'n' * (max+1)) # This test validates that PutItem replaces the entire item, including the # attribute 'b' used in the LSI key. The new item won't have 'b', so it should # be removed from the index. def test_lsi_put_overwrites_lsi_column(test_table_lsi_1): p = random_string() c = random_string() b = random_string() key = {'p': p, 'c': c} item = {**key, 'b': b} # Create an item with the LSI key column 'b'. test_table_lsi_1.put_item(Item=item) assert test_table_lsi_1.get_item(Key=key, ConsistentRead=True)['Item'] == item # The item should be added to the index. assert_index_query(test_table_lsi_1, 'hello', [item], KeyConditions={ 'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b], 'ComparisonOperator': 'EQ'}}) # Replace the item with an empty item. This should delete 'b'. test_table_lsi_1.put_item(Item=key) assert test_table_lsi_1.get_item(Key=key, ConsistentRead=True)['Item'] == key # Validate that PutItem also removed the item from the LSI index. assert_index_query(test_table_lsi_1, 'hello', [], KeyConditions={ 'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b], 'ComparisonOperator': 'EQ'}}) def test_lsi_update_modifies_index(test_table_lsi_1): p = random_string() c = random_string() b1 = random_string() b2 = random_string() key = {'p': p, 'c': c} item = {**key, 'b': b1} # Create an item with the LSI key column 'b' set to b1. test_table_lsi_1.put_item(Item=item) assert test_table_lsi_1.get_item(Key=key, ConsistentRead=True)['Item'] == item assert_index_query(test_table_lsi_1, 'hello', [item], KeyConditions={'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}}) # Set b to b2 instead of b1. test_table_lsi_1.update_item(Key=key, AttributeUpdates={'b': {'Value': b2, 'Action': 'PUT'}}) assert test_table_lsi_1.get_item(Key=key, ConsistentRead=True)['Item'] == {**key, 'b': b2} # Validate that the item is no longer in the index under b1, but under b2. assert_index_query(test_table_lsi_1, 'hello', [], KeyConditions={ 'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b1], 'ComparisonOperator': 'EQ'}}) assert_index_query(test_table_lsi_1, 'hello', [{'p': p, 'c': c, 'b': b2}], KeyConditions={ 'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}, 'b': {'AttributeValueList': [b2], 'ComparisonOperator': 'EQ'}}) def test_lsi_delete_modifies_index(test_table_lsi_1): p = random_string() key = {'p': p, 'c': random_string()} item = {**key, 'b': random_string()} # Create an item with the LSI key column 'b'. test_table_lsi_1.put_item(Item=item) assert test_table_lsi_1.get_item(Key=key, ConsistentRead=True)['Item'] == item # The item should be added to the index. assert_index_query(test_table_lsi_1, 'hello', [item], KeyConditions={'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}}) # Delete the item. test_table_lsi_1.delete_item(Key=key) assert not 'Item' in test_table_lsi_1.get_item(Key=key, ConsistentRead=True) # Validate that the item is no longer in the index. assert_index_query(test_table_lsi_1, 'hello', [], KeyConditions={'p': {'AttributeValueList': [p], 'ComparisonOperator': 'EQ'}}) # This test verifies that DescribeTable shows the correct user-requested LSI # key even when Alternator had to add to the underlying materialized view an # "extra" clustering key (because Scylla's MV requires each base key column # to also be a key column in the view). It serves as a regression test for # issue #5320. # This is the LSI version of test_gsi.py::test_gsi_describe_table_schema_all # but the LSI test has far fewer options than the GSI test because: # * We know the base table must have both hash and sort key (in the test # test_lsi_wrong_no_sort_key() we verified that we can't add an LSI # to a base table which has just a hash key). # * The LSI must have the same hash key as the base table. # These constraints leave us just *two* options: The LSI either has the same # sort key as the base (not a very interesting case, but valid), or the LSI's # sort key is a non-key attribute in the base. So this test just needs to # create one base table with two LSIs to cover all options. def test_lsi_describe_table_schema_all(dynamodb): # If we are to use an LSI the base table must have both hash key and sort # key. Let's call them 'a', 'b': base_keys = ['a', 'b'] # The LSI key must have the same hash key as the base ('a'), must # have a range key, and that range key can either be 'b' or not-'b' # (for which we take 'x'). So we only have these two options for what # the LSI key might be: lsi_keys_options = [['a', 'b'], ['a', 'x']] # Create a base table with base_keys and the two LSIs with the # LSI key options we collected in lsi_keys_options key_schema=[ { 'AttributeName': base_keys[0], 'KeyType': 'HASH' }, { 'AttributeName': base_keys[1], 'KeyType': 'RANGE' } ] attribute_definitions = [ {'AttributeName': attr, 'AttributeType': 'S' } for attr in (base_keys + ['x']) ] lsis = [] for i, lsi_keys in enumerate(lsi_keys_options): lsi_key_schema=[ { 'AttributeName': lsi_keys[0], 'KeyType': 'HASH' }, { 'AttributeName': lsi_keys[1], 'KeyType': 'RANGE' } ] lsis.append({ 'IndexName': f'index{i}', 'KeySchema': lsi_key_schema, 'Projection': { 'ProjectionType': 'ALL' } }) with new_test_table(dynamodb, KeySchema=key_schema, AttributeDefinitions=attribute_definitions, LocalSecondaryIndexes=lsis) as table: # Check that DescribeTable shows the table and its LSIs correctly: got = table.meta.client.describe_table(TableName=table.name)['Table'] assert got['KeySchema'] == key_schema got_lsis = got['LocalSecondaryIndexes'] # We want to compare got_lsis to the original lsis, but got_lsis may # have extra attributes that DescribeTable added beyond what was # present in the origin table creation. So let's leave in got_lsis # only the columns that were present in lsis[0]. got_lsis = [ {k: v for k, v in got_lsi.items() if k in lsis[0]} for got_lsi in got_lsis ] # Use multiset to compare ignoring order assert multiset(got_lsis) == multiset(lsis)