You perhaps don't understand my question. My question is: original column value is '1_3_12_15_27_35', but it can't directly be used to dimension value, so it must be splited to 6 values [1, 3, 12, 15, 27, 35], and this values will be used to construct the rowkey, and origianl record row will be expanded to 6 times, it is too big. Is there a way to read ' 1_3_12_15_27_35' and automate split it to 6 values in distinct column and other step, use this values to create dimension dictionary and rowkey, and don't need to preprocess orignal data.
Li Yang <[email protected]>于2016年8月18日周四 下午6:47写道： > Depends on how you query/process the multi-value field, the answer will be > different. > > Could you share some query sample? > > On Wed, Aug 17, 2016 at 2:35 PM, 张天生 <[email protected]> wrote: > >> Can someone help me to answer this question? I was still waiting for >> answer. >> >> 张天生 <[email protected]>于2016年8月15日周一 上午11:28写道： >> >>> I have a dimension user_tags, it is a multi-value column, for example >>> the value is "1_3_12_15_27_35_...", it was seperated by "_". As i known, >>> kylin don't directly propress this multi-value column, it must preprocess >>> it to a single value column, but it will increase record count to 50~100 >>> times, the data is too big.So is there a way to deal with multi-value >>> dimension, it don't need to split the value to many record, in calculate >>> dimension cardinality, it can read original data and automate split the >>> value to multi-value and process, and it will save disk i/o and cpu >>> spending. >>> >> >
