Re: Can't start minicluster
Maybe the thrift be/generated-sources are out of sync with the source code? We had some kind of metastore scheme upgrade that caused the other one. Dimitris' instructions to fix them were: > To fix this without doing a full data reload, you can use the following command: > ${IMPALA_TOOLCHAIN}/cdh_components/hive-1.1.0-cdh5.13.0- SNAPSHOT/bin/schematool -upgradeSchema -dbType {type} > where type is one of 'postgres' or 'mysql', depending on your setup. On Sun, Jul 9, 2017 at 3:52 PM, Jim Applewrote: > I am getting the following message in FATAL when I try to start a > minicluster > > Check failed: _TImpalaQueryOptions_VALUES_TO_NAMES.size() == > TImpalaQueryOptions::DEFAULT_JOIN_DISTRIBUTION_MODE + 1 (57 vs. 56) > > Any ideas what is going on? I was actually trying to buildall.sh > -format_metastore -format_sentry_policy_db because I was seeing messages > like the following (in hive.log) when I tried to start the minicluster: > > org.postgresql.util.PSQLException: ERROR: column A0.SCHEMA_VERSION_V2 > does > not exist >
Re: IMPALA-4326 - split() function
(also commented on IMPALA-4326) For this functionality, I'd prefer to follow what Postgres does and use its well-named functions like string_to_array(). This becomes powerful when using the unnest() table function, which is defined and is part of the ANSI/ISO SQL:2016 spec (vs the non-standard lateral view explode Hive syntax). with t as ( select 42 as id, '1,2,3,4,5,6'::text as string_array ) select t.id, u.l from t, unnest(string_to_array(t.string_array,',')) as u(l); id | l +--- 42 | 1 42 | 2 42 | 3 42 | 4 42 | 5 42 | 6 On Mon, Jun 19, 2017 at 7:40 AM, Alexander Behmwrote: > Yes and no. Extending the UDF framework might be hard, but I think > implementing a built-in split() is feasible. We already have a built-in > Expr that returns an array type to implement unnest. > > On Mon, Jun 19, 2017 at 6:22 AM, Vincent Tran wrote: > > > This request appears to be blocked by the current UDF framework's > > limitation. > > As far as I can tell, functions can still only return simple scalar > types, > > right? > > >