# Functions
*
* Aggregation示例
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*
* 创建一个SearchIndex,为TEXT类型索引列自定义分词器
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*
* 通过BoolQuery进行复合条件查询。
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*
*创建一个SearchIndex,包含Col_Keyword和Col_Long两列,类型分别设置为字符串(KEYWORD)和整型(LONG)。
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*
*创建一个SearchIndex,为Aggregation和GroupBy的demo做准备
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*
*创建一个SearchIndex,包含Col_Keyword和Col_Long两列,类型分别设置为字符串(KEYWORD)和整型(LONG),设置按照Col_Long这一列预先排序。
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*
*创建一个含虚拟列SearchIndex
*包含Col_Keyword和Col_Long两个基础列,类型分别设置为字符串(KEYWORD)和整型(LONG)。
*Col_long_str 为虚拟列,类型为字符串(KEYWORD)映射原始列为Col_long
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*
CreateTimeseriesTableSample 创建一个时序表,其中表名为:timeseriesTableName,TTL为:timetolive。
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*
DeleteTimeseriesTableSample 删除实例中表名为timeseriesTableName的时序表
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*
* DescribeTimeseriesTableSample 获取时序表timeseriesTableName的元数据信息。
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*
* Col_GeoPoint是GeoPoint类型,查询表中Col_GeoPoint这一列的值在左上角为"10,0", 右下角为"0,10"的矩形范围内的数据。
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*
* 查询表中Col_GeoPoint这一列的值距离中心点不超过一定距离的数据。
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*
* 查询表中Col_GeoPoint这一列的值在一个给定多边形范围内的数据。
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*
* GetTimeseriesDataSample 根据timeseriesKey获取时序表中指定的时间线数据
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*
* GroupBy示例
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*
* ListTimeseriesTableSample 列出实例中所有时序表的元数据信息
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*
* 查询表中Col_Text这一列的值能够匹配"hangzhou shanghai"的数据,匹配条件为短语匹配(要求短语完整的按照顺序匹配),返回匹配到的总行数和一些匹配成功的行。
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*
* 查询表中Col_Keyword这一列的值能够匹配"hangzhou"的数据,返回匹配到的总行数和一些匹配成功的行。
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*
* ParallelScan多并发
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*
* ParallelScan单并发
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*
* 查询表中Col_Keyword这一列前缀为"hangzhou"的数据。
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*
* PutTimeseriesDataSample 向时序表中写入一个或多个时序数据。
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*
* 使用Token进行翻页读取。
* 如果SearchResponse返回了NextToken,可以使用这个Token发起下一次查询,
* 直到NextToken为空(nil),此时代表所有符合条件的数据已经读完。
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*
* QueryTimeseriesMetaSample 根据指定条件查询数据表中特定时间线的measurement、source、tag信息,其中查询条件可组合。
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*
* 查询表中Col_Long这一列大于3的数据,结果按照Col_Long这一列的值逆序排序。
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SQLCreateTableSample 目前Create Table创建的是mapping映射表.
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*
* 查询表中Col_Keyword这一列精确匹配"hangzhou"的数据。
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*
* 查询表中Col_Keyword这一列精确匹配"hangzhou"或"tablestore"的数据。
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*
* 动态修改schema
* 修改schema的索引必须以_reindex结尾
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*
* UpdateTimeseriesMetaSample 更新时间线中的Attributes信息。
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*
* UpdateTimeseriesTableSample 更新时序表的TTL参数
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*
* 使用通配符查询,查询表中Col_Keyword这一列的值匹配"hang*u"的数据
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*
* 为Aggregation和GroupBy测试插入数据
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# Constants
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