Re: drill 1.16 to 1.17 error with ODBC

The HDF5 plugin modified the protobufs but I wouldn’t think that would cause this. Sent from my iPhone > On Feb 5, 2020, at 17:30, Paul Rogers wrote: > > Did a quick check of the source code. The GetServerMetaResp protobuf message > has not changed recently. > > Does anyone on the team

Re: Drill Fragment setup time

Hi Paul, The total query execution time itself is not crossing 18 secs which includes 1.9 secs of planning time. But going through the profile to see where is the time being spent, we saw 6 secs for "setup time" like above. How different is "setup time" from planning time? Duration

Runtime Kotlin + Drill JDBC netty problem

TL;DR: my Maven Fu is failing and I'm encountering a bad transitive dependency... Sorry I couldn't keep this shorter. But I'll get right to the point: The Drill server is up ... but I've been struggling mightily to connect to it via JDBC called from a Kotlin web app. First of all, this

Re: drill 1.16 to 1.17 error with ODBC

Did a quick check of the source code. The GetServerMetaResp protobuf message has not changed recently. Does anyone on the team know if we changed any Protobuf messages and either added or removed non-optional fields? Thanks, - Paul On Wednesday, February 5, 2020, 1:31:06 PM PST,

Re: Requesting json file with schema

Hi, Welcome to the Drill mailing list. You are right. Drill is a SQL engine. It works best when the JSON input files represent rows and columns. Of course, JSON itself can represent arbitrary data structures: you can use it to serialize any Java structure you want. Relational tables and

Re: Drill Fragment setup time

Hi Aditya, While I cannot comment on MapR-DB in particular, I can say that, in general, Drill is designed for fairly large queries. There is a trade-off between the overhead of code gen and planning vs. the cost at runtime. Drill tends to invest more in up-front planning and code gen to

Re: Any pointers to launch drill bit programmatically

Hi Hema, Welcome to Drill! Drill's primary use case is to run distributed queries across multiple nodes. For that, Drill generally runs as a stand-alone process, perhaps launched by YARN, Docker, K8s or your own scripts. Although Drill runs in embedded mode, this is mostly to provide a "quick

Re: drill 1.16 to 1.17 error with ODBC

Hi Rafael, Can you share the python code? -- C > On Feb 5, 2020, at 12:48 PM, Jaimes, Rafael - 0993 - MITLL > wrote: > > I had Drill 1.16 running in embedded mode and it was running without error. > > After just switching to the 1.17 tarball and running in embedded mode, I seem > to get

drill 1.16 to 1.17 error with ODBC

I had Drill 1.16 running in embedded mode and it was running without error. After just switching to the 1.17 tarball and running in embedded mode, I seem to get these warnings after running queries using ODBC and Python (always 4 of them, exact same message): [libprotobuf ERROR

Requesting json file with schema

Hi, Some JSON file are complex and containing differents "tree struct". If these file are big it will take too much time for drill to align the structures (and even worse sometimes fail). In spark it's possible to force a schema when reading a file to avoid long or useless treatment of align

Drill Fragment setup time

Team, Is there a way to reduce the "setup time" for a minor fragment? In my case, it's Drill on Mapr-db JSON table. As per documentation, it is time consumed for "runtime code generation and opening a file". While going through a query profile i see below: Minor Fragment Hostname Setup Time