We have UDFs in a few locations and today we noticed they died in performance. This seems to be caused by Unity Catalog.Test environment 1:Databricks Runtime Environment: 14.3 / 15.1Compute: 1 master, 4 nodesPolicy: UnrestrictedAccess Mode: SharedTes...
Hi @Erik_L ,
It appears that you’re experiencing performance issues related to Unity Catalog in your Databricks environment.
Let’s explore some potential reasons and solutions:
Mismanagement of Metastores:
Unity Catalog, with one metastore per re...
Hi, It seems that when databricks-connect is installed, pyspark is at the same time modified so that it will not anymore work with local master node. This has been especially useful in testing, when unit tests for spark-related code without any remot...
Hi @htu,
When you install Databricks Connect, it modifies the behaviour of PySpark in a way that prevents it from working with the local master node. This can be frustrating, especially when you’re trying to run unit tests for Spark-related code w...
Just want to post this issue we're experiencing here in case other people are facing something similar. Below is the wording of the support ticket request I've raised:SQL code that has been working is suddenly failing due to syntax errors today. Ther...
The point that we've got to with this is that MS Support / Databricks have acknowledged that they did something and are working on a fix. "The issue occurred due to the regression in the recent DBR maintenance release...Our engineering team is workin...
Hello,I have a Job A that runs a Job B, and Job A defines a globalTempView and I would like to somehow access it in the child job. Is that in anyway possible ? Can the same cluster be used for both jobs ? If it is not possible, does someone know of a...
Hello @Kaniz ,thank you for the very detailed answer. If I understand correctly there is no way to do this using temp views and using a Job Cluster ? I need in the case to use the same All-purpose for all my tasks in order to remain in the same spar...
Hi, I am loading data from a kinesis data stream using DLT. CREATE STREAMING TABLE Consumers_kinesis_2
(
...,
unbase64(data) String,
...
)
AS
SELECT * FROM STREAM read_kinesis (...) Is it possible to directly cast, unbase64, and/or transform the resu...
Hi @Mathias_Peters, When working with Amazon Kinesis Data Analytics, you can indeed transform data before writing it into a streaming table.
Let’s explore some options:
Unbase64 Transformation:
To decode Base64-encoded data, you can use the unba...
I'm recieving this error from autoloader. It seems to be stuck on this one file. I don't care when it was read and last modified, I just want to ingest it. Any ideas?java.io.IOException: Read old version of file s3a://<file-path>.json. Read modificat...
Hi @stevenayers-bge, The error message indicates that the file you’re trying to read is an old version, and there’s a discrepancy between the read modification time and the latest modification time.
Let’s explore some potential solutions based on ...
Hi,I have configured 20 different workflows in Databricks. All of them configured with job cluster with different name. All 20 workfldows scheduled to run at same time. But even configuring different job cluster in all of them they run sequentially w...
Hi @jainshasha,
Running multiple workflows in parallel with their own job clusters in Databricks can be achieved by following the right configuration.
Let’s explore some options:
Shared Job Clusters:
To optimize resource usage with jobs that orch...
Hey guys, I'm trying to find what are the options we can pass to spark_conf.spark.databricks.cluster.profileI know looking around that some of the available configs are singleNode and serverless, but there are others?Where is the documentation of it?...
Hi @LeoGaller , The spark_conf.spark.databricks.cluster.profile configuration in Databricks allows you to specify the profile for a cluster.
Let’s explore the available options and where you can find the documentation.
Available Profiles:
Sing...
I am having an issue where when I do a shallow clone using :create or replace table `catalog_a_test`.`schema_a`.`table_a` shallow clone `catalog_a`.`schema_a`.`table_a` I get:[TABLE_OR_VIEW_NOT_FOUND] The table or view catalog_a_test.schema_a.table_a...
Hi StevenThis is really a strange issue. First let's exclude some possible causes for this. We need to check the following:- The permission to table A and Catalog B. take a look at the following link to check what permission is needed: https://docs.d...
Hey Everyone,I've built a very simple pipeline with a single DLT using auto ingest, and it works, provided I don't specify the output location. When I build the same pipeline but set UC as the output location, it fails when setting up S3 notification...
Hey @Babu_Krishnan I was! I had to reach out to my Databricks support engineer directly and the resolution was to add "cloudfiles.awsAccessKey" and "cloudfiles.awsSecretKey" to the params as in the screenshot below (apologies, i don't know why the sc...
I am trying to unpivot a PySpark DataFrame, but I don't get the correct results.Sample dataset:# Prepare Data
data = [("Spain", 101, 201, 301), \
("Taiwan", 102, 202, 302), \
("Italy", 103, 203, 303), \
("China", 104, 204, 304...
You can also use backticks around the column names that would otherwise be recognised as numbers.from pyspark.sql import functions as F
unpivotExpr = "stack(3, '2018', `2018`, '2019', `2019`, '2020', `2020`) as (Year, CPI)"
unPivotDF = df.select("C...
May be I am new to Databricks that's why I have confusion.Suppose I have worker memory of 64gb in Databricks job max 12 nodes...and my job is failing due to Executor Lost due to 137 (OOM if found on internet).So, to fix this I need to increase execut...
Hello @amitkmaurya ,
Increasing compute resources may not always be the best strategy. To gain more insights into each executor's memory usage, check the cluster metrics tab and Spark UI for your cluster. If one executor has a much higher memory usag...
Hi Team,Recently we had created new Databricks project/solution (based on Medallion architecture) having Bronze-Silver-Gold Layer based tables. So we have created Delta-Live-Table based pipeline for Bronze-Layer implementation. Source files are Parqu...
Hello @Devsql ,
It appears that you are creating DLT bronze tables using a standard spark.read operation. This may explain why the DLT table doesn't include "new files" during a REFRESH operation.
For incremental ingestion of bronze layer data into y...
I deleted for mistake some records from a streaming table, and of course, the streaming job stopped working. So I restored the table at the version before the delete was done, and attempted to restart the job using the startingVersion to the new vers...
Hello @6502,
It appears you've used the `startingVersion` parameter in your streaming query, which causes the stream to begin processing data from the version prior to the DELETE operation version. However, the DELETE operation will still be processe...
Hi,I have one table that changes the name every 60 days. The name simple increases the number version, for example:* Firtst 60 days: table_name_v1. After 60 days: table_name_v2 and so on.What i want is to query the table wich name returned in the que...
The simpliest way would be propably using spark.sql%py
tbl_name = 'table_v1'
df = spark.sql(f'select * from {tbl_name}')
display(df) From there, You can simply create temporary view:%py
df.createOrReplaceTempView('table_act')and query it using SQL st...