Can you try something like this:- String querySql= "SELECT * FROM ENVI_DATA where PATIENT_ID=?"; RowMapper<EnviData> rowMapper = newRowMapper<EnviData>(){ @Override public EnviData mapRow(ResultSet rs,int rowNum) throwsSQLException{ EnviData data =new EnviData(); data.setPatientId(rs.getString(1)); data.setUserRoutes(rs.getArray(7).getArray()); } return jdbcTemplate.update(querySql, rowMapper, id); ... View more

If these are the only property you need from hbase-site.xml , you can create a connection by passing the properties in props. Properties props = new Properties(); props.setProperty(QueryServices.IS_NAMESPACE_MAPPING_ENABLED, Boolean.toString(true)); props.setProperty(QueryServices.IS_SYSTEM_TABLE_MAPPED_TO_NAMESPACE, Boolean.toString(false)); Connection conn = DriverManager.getConnection(getUrl(), props); ... View more

have you confirmed that "ER_V13_SPLIT_511_GZ_V2_METERKEY" doesn't appear when you do !tables on sqlline. (or you can query system.catalog if any link for this index exists) For a workaround:- you can try creating "ER_V13_SPLIT_511_GZ_V2_METERKEY" from HBase shell using same table descriptor of data table but with just different table name. ... View more

you can read the data from Phoenix using phoenix-spark connector and the using spark native APIs , you can join (or union) those data frames into single data frame. ... View more

Yeah, it seems like a bug that hint is ignored in the case of global functional index. As a workaround, you can include all columns in the covered index (I mean option#2). ... View more

Yeah, it seems like a bug that hint is ignored in the case of global functional index. As a workaround, you can include all columns in covered index (I mean option#2). ... View more

Select * is projecting all the columns, option1 suggest you can project only your pk columns and indexed column if you really want to use the non-covered global functional index. Ah, you mean, hint is also not helping. Let me check this at my side. ... View more

SELECT /*+ INDEX(S1.TABLE1 IDX_UPPER) */ * FROM S1.TABLE1 WHERE UPPER(FIRST_NAME) = 'ABC'; It looks like that you are trying to project all the columns of the table but your functional index is not covered(means does not include all the columns of the table). You have following options:- * Either project the pk columns and function select pk,pk2,pk3.., UPPER(FIRST_NAME) from S1.table1 * Or create a covered index. CREATE INDEX IDX_UPPER ON S1.TABLE1 (UPPER(FIRST_NAME)INCLUDE(COL1,COL2...) * Or if you are sure that you will have fewer rows for UPPER(FIRST_NAME) , then you can create non-covered local index.(this will fetch the remaining columns from data table automatically) CREATE LOCAL INDEX IDX_UPPER ON S1.TABLE1 (UPPER(FIRST_NAME) ... View more

Is there a table showing how to compare different keyword in explain plans? Ex: “PARALLEL 1-WAY ROUND ROBIN FULL SCAN” versus “PARALLEL 9-WAY FULL SCAN”, which one would be faster if everything else was the same? https://phoenix.apache.org/tuning_guide.html Is there a way to determine if all of my RegionServers are being used during the execution of a particular query? Currently with explain plan ,there is no way to determine that all your regionservers are getting used for the query , although if there is full table scan ,then all the regions will be scanned but still you can't be sure that all regionservers are getting used as it depends upon your balancer policy and the distribution can be checked from master UI. What is the 9-CHUNK in “CLIENT 9-CHUNK 4352857 ROWS 943718447 BYTES” mean? Are more CHUNKs better or worse? https://phoenix.apache.org/tuning_guide.html What is the impact of using functions, such as HOUR(ts) on query execution time? Is the impact 1%, 10%, 50%, etc…? it depends , for eg:- if you are applying hour(ts) where 'ts' is the first part of the primary key and you don't have functional index on it, then the query may be turned into full table scan where the impact range could be anything. although, processing time of evaluating the function on the column value depends upon the function complexity and no. of rows you are scanning. ... View more

You can set hive.merge.mapredfiles to true , it will run the another mapreduce job after the original one to combine all files into one. https://cwiki.apache.org/confluence/display/Hive/AdminManual+Configuration ... View more

You can use hive storage handler or pig or spark to do that. https://phoenix.apache.org/hive_storage_handler.html https://phoenix.apache.org/pig_integration.html https://phoenix.apache.org/phoenix_spark.html ... View more