Apache Paimon Hive引擎解析

HIve 引擎

Paimon 当前���持 Hive 的 3.1, 2.3, 2.2, 2.1 和 2.1-cdh-6.3 版本。

1.执行引擎

当使用Hive Read数据时，Paimon 支持 MR 和 Tez 引擎, 当使用Hive Write数据时，Paimon支持MR引擎，如果使用 beeline，需要重启hive cluster。

2.安装

Version           JarHive 3.1        paimon-hive-connector-3.1-0.7.0-incubating.jarHive 2.3        paimon-hive-connector-2.3-0.7.0-incubating.jarHive 2.2        paimon-hive-connector-2.2-0.7.0-incubating.jarHive 2.1        paimon-hive-connector-2.1-0.7.0-incubating.jarHive 2.1-cdh-6.3paimon-hive-connector-2.1-cdh-6.3-0.7.0-incubating.jar

将Jar添加到Hive中有以下方法：

• 在Hive的根目录下创建一个auxlib文件夹，并将paimon-hive-connector-0.7.0-incubating.jar复制到auxlib中。
• 将jar复制到Hive可访问的路径，然后使用add jar /path/to/paimon-hive-connector-0.7.0-incubating.jar在Hive中启用paimon支持，注意，不建议使用这种方法，如果使用MR引擎运行Join语句，可能报错org.apache.hive.com.esotericsoftware.kryo.kryoexception: unable to find class。

  注意：

  • 如果使用HDFS，请确保设置了环境变量HADOOP_HOME或HADOOP_CONF_DIR。
  • 如果使用hive cbo优化器，可能会导致一些不正确的查询结果，例如使用not null谓词查询struct类型，可以通过set hive.cbo.enable=false;命令禁用cbo优化器。

    3.Flink SQL: 使用 Paimon Hive Catalog

    使用paimon Hive catalog，可以通过Flink create，drop，select 和 insert 到 paimon 表中，这些操作直接影响对应的Hive metastore，以这种方式创建的表可以直接从Hive访问。

    步骤一：

    准备Flink Hive Connector Bundled Jar。

    步骤二：

    在Flink SQL Client中执行以下Flink SQL脚本，以定义Paimon Hive catalog并创建Table。

    -- Flink SQL CLI-- Define paimon Hive catalogCREATE CATALOG my_hive WITH (  'type' = 'paimon',  'metastore' = 'hive',  -- 'uri' = 'thrift://:', default use 'hive.metastore.uris' in HiveConf  -- 'hive-conf-dir' = '...', this is recommended in the kerberos environment  -- 'hadoop-conf-dir' = '...', this is recommended in the kerberos environment  -- 'warehouse' = 'hdfs:///path/to/table/store/warehouse', default use 'hive.metastore.warehouse.dir' in HiveConf);-- Use paimon Hive catalogUSE CATALOG my_hive;-- Create a table in paimon Hive catalog (use "default" database by default)CREATE TABLE test_table (  a int,  b string);-- Insert records into test tableINSERT INTO test_table VALUES (1, 'Table'), (2, 'Store');-- Read records from test tableSELECT * FROM test_table;/*+---+-------+| a |     b |+---+-------+| 1 | Table || 2 | Store |+---+-------+*/

    4.Hive SQL: 访问已经在 Hive metastore 中的 Paimon Tables

    在Hive CLI中运行以下Hive SQL访问创建的表。

    -- Assume that paimon-hive-connector--0.7.0-incubating.jar is already in auxlib directory.-- List tables in Hive-- (you might need to switch to "default" database if you're not there by default)SHOW TABLES;/*OKtest_table*/-- Read records from test_tableSELECT a, b FROM test_table ORDER BY a;/*OK1Table2Store*/-- Insert records into test table-- Note tez engine does not support hive write, only the hive engine is supported.INSERT INTO test_table VALUES (3, 'Paimon');SELECT a, b FROM test_table ORDER BY a;/*OK1Table2Store3Paimon*/-- time travelSET paimon.scan.snapshot-id=1;SELECT a, b FROM test_table ORDER BY a;/*OK1Table2Store3Paimon*/SET paimon.scan.snapshot-id=null;

    5.Hive SQL: 创建新的 Paimon Tables

    在Hive CLI中运行以下Hive SQL创建新的paimon表。

    -- Assume that paimon-hive-connector-0.7.0-incubating.jar is already in auxlib directory.-- Let's create a new paimon table.SET hive.metastore.warehouse.dir=warehouse_path;CREATE TABLE hive_test_table(    a INT COMMENT 'The a field',    b STRING COMMENT 'The b field')STORED BY 'org.apache.paimon.hive.PaimonStorageHandler';

    6.Hive SQL: 通过外部表访问 Paimon 的表

    在Hive中将paimon表注册为外部表，在Hive CLI中运行以下Hive SQL来访问。

    -- Assume that paimon-hive-connector-0.7.0-incubating.jar is already in auxlib directory.-- Let's use the test_table created in the above section.-- To create an external table, you don't need to specify any column or table properties.-- Pointing the location to the path of table is enough.CREATE EXTERNAL TABLE external_test_tableSTORED BY 'org.apache.paimon.hive.PaimonStorageHandler'LOCATION '/path/to/table/store/warehouse/default.db/test_table';    -- In addition to the way setting location above, you can also place the location setting in TBProperties-- to avoid Hive accessing Paimon's location through its own file system when creating tables.-- This method is effective in scenarios using Object storage,such as s3.CREATE EXTERNAL TABLE external_test_tableSTORED BY 'org.apache.paimon.hive.PaimonStorageHandler'TBLPROPERTIES ( 'paimon_location' ='s3://xxxxx/path/to/table/store/warehouse/default.db/test_table');-- Read records from external_test_tableSELECT a, b FROM external_test_table ORDER BY a;/*OK1Table2Store*/-- Insert records into test tableINSERT INTO external_test_table VALUES (3, 'Paimon');SELECT a, b FROM external_test_table ORDER BY a;/*OK1Table2Store3Paimon*/

    7.Hive 和 Paimon 的类型映射

    列出了Hive和Paimon之间所有支持的类型转换，Hive的所有数据类型都可以在org.apache.hadoop.hive.serde2.typeinfo中找到。

    Hive Data Type	Paimon Data Type	Atomic Type
    StructTypeInfo	RowType	false
    MapTypeInfo	MapType	false
    ListTypeInfo	ArrayType	false
    PrimitiveTypeInfo("boolean")	BooleanType	true
    PrimitiveTypeInfo("tinyint")	TinyIntType	true
    PrimitiveTypeInfo("smallint")	SmallIntType	true
    PrimitiveTypeInfo("int")	IntType	true
    PrimitiveTypeInfo("bigint")	BigIntType	true
    PrimitiveTypeInfo("float")	FloatType	true
    PrimitiveTypeInfo("double")	DoubleType	true
    CharTypeInfo(length)	CharType(length)	true
    PrimitiveTypeInfo("string")	VarCharType(VarCharType.MAX_LENGTH)	true
    VarcharTypeInfo(length)	VarCharType(length), length is less than VarCharType.MAX_LENGTH	true
    PrimitiveTypeInfo("date")	DateType	true
    PrimitiveTypeInfo("timestamp")	TimestampType	true
    DecimalTypeInfo(precision, scale)	DecimalType(precision, scale)	true
    PrimitiveTypeInfo("binary")	VarBinaryType, BinaryType	true