1.使用scylla镜像来启动scyllaDB

2.在cqlsh中操作scyllaDB

在cqlsh中可以使用CQL (the Cassandra Query Language) 来对scyllaDB做一些基本操作

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sh-4.2# cqlsh

Connected to at 172.17.0.3:9042.

[cqlsh 5.0.1 | Cassandra 3.0.8 | CQL spec 3.3.1 | Native protocol v4]

Use HELP for help.

cqlsh>

参考：CQLSh: the CQL shell

3.scyllaDB的数据存储于table当中，而table由keyspace分组

创建一个叫test的keysapce

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cqlsh> CREATE KEYSPACE IF NOT EXISTS test WITH REPLICATION = {'class': 'SimpleStrategy','replication_factor':1};

cqlsh> describe keyspaces;

system_schema system_auth system system_distributed test system_traces

REPLICATION参数指定了备份策略，使用了REPLICATION后必须指定class，其中class有SimpleStrategy，NetworkTopologyStrategy，在这里由于是单机测试，所以我指定副本数量是1

创建表

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cqlsh> use test;

cqlsh:test>

CREATE TABLE demo (

user_id int,

str text,

mtime timestamp,

PRIMARY KEY (user_id, mtime)

) WITH CLUSTERING ORDER BY (mtime DESC);

cqlsh:test> DESCRIBE TABLES

demo

cqlsh:test>

PRIMARY KEY参数指定了主键，会按照user_id，mtime的顺序来排列key

CLUSTERING参数指定了mtime按照降序排列

4.插入数据

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INSERT INTO demo (

user_id,str,mtime

) VALUES

(6,'test','2021-10-09 07:00:00')

using TTL 86400;

可以看到相同的key user_id会聚合到一起，相同的user_id中mtime按照降序排列

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cqlsh:test> select * from demo;

user_id | mtime | str

---------+---------------------------------+-------

5 | 2021-10-09 02:00:00.000000+0000 | Panda

1 | 2021-10-09 04:00:00.000000+0000 | Kay

1 | 2021-10-01 02:00:00.000000+0000 | Kay

2 | 2021-10-09 03:00:00.000000+0000 | Snail

2 | 2021-10-01 02:00:00.000000+0000 | Snail

6 | 2021-10-09 07:00:00.000000+0000 | test

(6 rows)

参考：Data Definition　

5.部署scylla集群

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docker run --name scylla -p 9042:9042 -p 9160:9160 -p 10000:10000 -p 9180:9180 -v /var/lib/scylla:/var/lib/scylla -d scylladb/scylla

docker run --name scylla-node2 -p 8042:9042 -p 8160:9160 -p 1000:10000 -p 8180:9180 -v /var/lib/scylladb2:/var/lib/scylla -d scylladb/scylla --seeds="$(docker inspect --format='{{ .NetworkSettings.IPAddress }}' scylla)"

docker run --name scylla-node3 -p 10042:9042 -p 10160:9160 -p 1100:10000 -p 10180:9180 -v /var/lib/scylladb3:/var/lib/scylla -d scylladb/scylla --seeds="$(docker inspect --format='{{ .NetworkSettings.IPAddress }}' scylla)"

docker run --name scylla-node4 -p 11042:9042 -p 11160:9160 -p 1200:10000 -p 11180:9180 -v /var/lib/scylladb4:/var/lib/scylla -d scylladb/scylla --seeds="$(docker inspect --format='{{ .NetworkSettings.IPAddress }}' scylla)"

6.查看集群状态

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[root@6a30e1b8fc71 /]# nodetool status

Using /etc/scylla/scylla.yaml as the config file

Datacenter: datacenter1

=======================

Status=Up/Down

|/ State=Normal/Leaving/Joining/Moving

--  Address     Load       Tokens       Owns    Host ID                               Rack

UN 172.17.0.2 1.49 MB 256 ? eaee8765-450d-4d4e-a7b5-2ed4c6b20df3 rack1

UN 172.17.0.5 1.04 MB 256 ? 17153bb7-f4f1-4436-bc49-f1eca3409040 rack1

UN 172.17.0.4 1.03 MB 256 ? 25fd6224-7edc-4161-bf49-ba6fe51c9f73 rack1

UN 172.17.0.6 1.04 MB 256 ? 3d5757d2-dc5f-4ba4-8d90-e02eb9d4c255 rack1

Note: Non-system keyspaces don't have the same replication settings, effective ownership information is meaningless

7.查看表状态

1	`nodetool tablestats my_ks.my_tb`

8.增加字段

1	`ALTER TABLE xx.xx ADD col_name col_type;`

使用spark读写scyllaDB

由于scyllaDB兼容cassandra API，所以可以参考：

1	`https://docs.microsoft.com/en-us/azure/cosmos-db/cassandra/spark-create-operations`

ITPub博客

scyllaDB基本使用

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