UDT列删除导致Cassandra损坏

时间：2018-08-26 11:51:21

标签： cassandra cql

我们生产的Cluster Cassandra版本是：[cqlsh 5.0.1 |卡桑德拉3.11.3 | CQL规范3.4.4 |原生协议v4]

重新启动Cassandra节点后，Cassandra没有启动，并显示了以下错误：

INFO  [main] 2018-08-22 15:30:04,082 CommitLogReader.java:105 - Skipping playback of empty log: CommitLog-6-1534951460541.log
DEBUG [main] 2018-08-22 15:30:04,082 CommitLogReader.java:273 - Reading /var/lib/cassandra/commitlog/CommitLog-6-1527416281330.log (CL version 6, messaging version 11, compression null)
INFO  [Service Thread] 2018-08-22 15:30:06,501 GCInspector.java:284 - ParNew GC in 216ms.  CMS Old Gen: 10906456 -> 31114600; Par Eden Space: 859045888 -> 0; Par Survivor Space: 29166056 -> 43187600
DEBUG [main] 2018-08-22 15:30:06,673 CommitLogReader.java:264 - Finished reading /var/lib/cassandra/commitlog/CommitLog-6-1527416281330.log
DEBUG [main] 2018-08-22 15:30:06,674 CommitLogReader.java:273 - Reading /var/lib/cassandra/commitlog/CommitLog-6-1527416281331.log (CL version 6, messaging version 11, compression null)
DEBUG [main] 2018-08-22 15:30:08,009 CommitLogReader.java:264 - Finished reading /var/lib/cassandra/commitlog/CommitLog-6-1527416281331.log
DEBUG [main] 2018-08-22 15:30:08,009 CommitLogReader.java:273 - Reading /var/lib/cassandra/commitlog/CommitLog-6-1527416281332.log (CL version 6, messaging version 11, compression null)
ERROR [main] 2018-08-22 15:30:08,610 JVMStabilityInspector.java:102 - Exiting due to error while processing commit log during initialization.
org.apache.cassandra.db.commitlog.CommitLogReadHandler$CommitLogReadException: Unexpected error deserializing mutation; saved to /tmp/mutation1296995018372874453dat.  This may be caused by replaying a mutation against a table with the same name but incompatible schema.  Exception follows: java.io.IOError: java.io.EOFException: EOF after 45 bytes out of 33554712
    at org.apache.cassandra.db.commitlog.CommitLogReader.readMutation(CommitLogReader.java:471) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.db.commitlog.CommitLogReader.readSection(CommitLogReader.java:404) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.db.commitlog.CommitLogReader.readCommitLogSegment(CommitLogReader.java:251) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.db.commitlog.CommitLogReader.readAllFiles(CommitLogReader.java:132) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.db.commitlog.CommitLogReplayer.replayFiles(CommitLogReplayer.java:137) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.db.commitlog.CommitLog.recoverFiles(CommitLog.java:177) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.db.commitlog.CommitLog.recoverSegmentsOnDisk(CommitLog.java:158) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.service.CassandraDaemon.setup(CassandraDaemon.java:324) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.service.CassandraDaemon.activate(CassandraDaemon.java:602) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.service.CassandraDaemon.main(CassandraDaemon.java:691) [apache-cassandra-3.11.3.jar:3.11.3]

移出CommitLogs（这会导致数据丢失）之后，Cassandra确实启动了，但是对某些表的查询失败，并显示

ReadFailure: Error from server: code=1300 [Replica(s) failed to execute read] message="Operation failed - received 0 responses and 1 failures" info={'failures': 1, 'received_responses': 0, 'required_responses': 1, 'consistency': 'ONE'}

和system.log：

WARN  [ReadStage-2] 2018-08-26 11:04:34,091 AbstractLocalAwareExecutorService.java:167 - Uncaught exception on thread Thread[ReadStage-2,10,main]: {}
java.lang.RuntimeException: org.apache.cassandra.io.sstable.CorruptSSTableException: Corrupted: /var/lib/cassandra/data/policy/rule-83f10050a91f11e890846d2c86545d91/mc-52-big-Data.db
    at org.apache.cassandra.service.StorageProxy$DroppableRunnable.run(StorageProxy.java:2601) ~[apache-cassandra-3.11.3.jar:3.11.3]
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) ~[na:1.8.0_171]
    at org.apache.cassandra.concurrent.AbstractLocalAwareExecutorService$FutureTask.run(AbstractLocalAwareExecutorService.java:162) ~[apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.concurrent.AbstractLocalAwareExecutorService$LocalSessionFutureTask.run(AbstractLocalAwareExecutorService.java:134) [apache-cassandra-3.11.3.jar:3.11.3]
    at org.apache.cassandra.concurrent.SEPWorker.run(SEPWorker.java:109) [apache-cassandra-3.11.3.jar:3.11.3]
    at java.lang.Thread.run(Thread.java:748) [na:1.8.0_171]

经过调查，我很确定可以通过以下步骤重现该错误：

  1. 创建一个全新的Cassandra docker容器：docker stop cassandra-prod; docker rm cassandra-prod; docker run -d --name cassandra-prod -p 9042：9042 cassandra：3.11.3; docker exec -it cassandra-prod bash
  2. 创建密钥空间
  3. 创建UDT
  4. 使用列类型创建表，该列是先前创建的UDT
  5. 在表中插入多行
  6. 删除UDT列
  7. 重启Cassandra：docker stop cassandra-prod; docker start cassandra-prod; docker exec -it cassandra-prod bash
  8. 对该表执行SELECT查询


DROP KEYSPACE IF EXISTS my_ks;
CREATE KEYSPACE my_ks WITH replication = {'class':'SimpleStrategy', 'replication_factor':1};
CREATE TYPE my_ks.my_type(column1 text);

CREATE TABLE my_ks.my_table (
  id uuid primary key,
  mt my_type
);

INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});
INSERT INTO my_ks.my_table(id, mt) VALUES(uuid(), {column1 : 'value1'});

ALTER TABLE my_ks.my_table DROP mt;

以下步骤重现了CorruptSSTableException，但未重现CommitLogReadHandler $ CommitLogReadException。
顺便说一句，在Cassandra 3.11.1上，使用上述步骤未再现该错误。

1 个答案:

答案 0 :(得分：2)

在Cassandra 4.0中，将禁止删除（冻结）非冻结的用户定义类型列。引发的错误是

import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.svm import LinearSVC

categories = [
    'alt.atheism',
    'talk.religion.misc',
    'comp.graphics',
    'sci.space']

dataset = fetch_20newsgroups(subset='all', categories=categories,
                             shuffle=True, random_state=42)
vectorizer = CountVectorizer()




# Just to replace classes from integers to their actual labels, 
# you can use anything as you like in y
y = []
mapping_dict = dict(enumerate(dataset.target_names))
for i in dataset.target:
    y.append(mapping_dict[i])

# Learn the words from data
X = vectorizer.fit_transform(dataset.data)

clf = LinearSVC(random_state=42)
clf.fit(X, y)

plot_coefficients(clf, vectorizer.get_feature_names())

我在后备箱上进行了测试。不幸的是，这对于早期版本（<4.0）尚不可用。

在您的udt列中使用InvalidRequest: Error from server: code=2200 [Invalid query] message="Cannot drop non-frozen column mt of user type my_type" 应该可以解决此问题（我在3.11.3中进行了测试）（但是无法更改列的类型）。

frozen

为此问题也打开了CASSANDRA-14673。

相关问题
最新问题