Voice of the DBA

Author: way0utwest

  • My 2024 in Data: Music

    This is my last week of the year working (I guess I come back on the 30th for a minute), so I decided to do some analysis of my year. I like data and numbers, so I’m looking at a few aspects of life this year with data I’ve compiled from previous years.

    This is the end of the week and I’m looking at music, which is a big part of my life.

    Spotify Wrapped

    I listen a lot on Spotify. On my phone, in the car, even at my desk. I do some YouTube at times, and I have my local library from days past loaded into the Spotify app, but mostly I’m streaming.

    • Minutes: 36916 (25.6 days)
    • Songs: 3,598
    • Biggest day: 657 minutes (10 hours, flying DEN-LAX-SYD)
    • Ghost in my Guitar most played, 62 times this year
    • Artists: 1536, Zach Bryan being the top one for me (almost 10% of my minutes)
      • #2 – Beatles
      • #3 – Kanye
      • #4 – John Mayer
      • #5 – Linkin Park

    When I look back, this is slightly less than last year. About 40 minutes less streaming, about 100 less artists, about 200 less songs. More repeats.

    Interesting that my top artists were similar. John Mayer, Zach Bryan, The Beatles. This year Kanye and Linkin Park replaced U2 and Chris Stapleton. Previous years had Jay-Z, Tupac, and Kenny Chesney in there.

    I like to think I explore different music, but not a lot (apparently). I tend to listen to familiar things and keep some playlists around for a long time.

    Guitar

    Another part of my music is that I play guitar to relax. I keep an acoustic Sweetwater guitar by my bed and will play many nights for a bit to unwind. I love Redgate has a few in our Cambridge lobby, though they are very cheap, not comfortable ones, but they work.

    This year I also bought a Lava Me Play smart guitar in the summer, which I’ve taken on some vacations. It sits by my desk and I’ll take a break and strum something during the way. I haven’t done much with the “smart” features, which helped me learn I really just wanted a second, smaller acoustic.

    Top songs I’ve worked on this year (in no order):

    • Mechanical Bull – Zach Bryan
    • 28 – Zach Bryan
    • With or without you – U2
    • 3×5 – John Mayer
    • Jersey Giant – Tyler Childers
    • You’ve Got To Hide Your Live – The Beatles
    • Hallelujah – Jeff Buckley
    • If I Ain’t Got You – Alicia Keys

    I’ve done a few more lighlty, but these are some I’ve played a lot, a few I’m still trying to get to sound vaguely like something you recognize.

    2024 was a fun year of music for me, and I’m looking forward to 2025.

  • A New Word: Suente

    suente– n. the state of being so familiar with someone that you can be in a room with them without thinking, without holding anything back, or without having to say a word – to the extent that you have to remind yourself that they’re a different being entirely, that brushing hair away from their eyes won’t help you see any better.

    This makes me think of the familiarity I have with my wife or kids or a few close friends. We don’t need to talk, and we know what the others are thinking based on the situation or body language. We can sit in a room reading, relaxing, watching something, listening to music, and we feel both comfortable and close.

    I love the suente and I’m glad it’s with few people.

    From the Dictionary of Obscure Sorrows

  • My 2024 in Data: Health and Workouts

    This is my last week of the year working (I guess I come back on the 30th for a minute), so I decided to do some analysis of my year. I like data and numbers, so I’m looking at a few aspects of life this year with data I’ve compiled from previous years.

    Today we look at my health (somewhat) and exercise. That’s a big part of my life and I dedicate a lot of time to taking care of myself.

    Health

    I don’t want to disclose too much, but I feel fairly healthy. I have some age-related things that are annoying, but in general, I can live my life. This year (2024) was the first time since ankle surgery (2022), that I felt my balance was really good on the surgical ankle. That was nice to have it feel over the summer that it was back to full strength.

    I don’t have history (that I know of) of heart issues, but I like tracking my heart. I use a Garmin Forerunner 645, which seems to be accurate the few times I’m also hooked up to a doctor’s machine.

    My yearlong resting heart rate is: 52bpm. Sightly high, as I’d like it at 50 or below, but I’ve had some stressful travel stretches, and I think that’s made things slightly worse.

    My avg. high is 128, which is mostly from exercise, though I don’t know what to think about that number as an average.

    My one year sleep average is 8h35m a night. Pretty good, though I think the watch sometime catches me at night or in the morning as lightly sleeping when I’m reading. Still, it’s good I’m in bed for a nice stretch most nights.

    I struggle with weight as I travel. I was trying to stay 220-225, which I did well with in 2023. This year, with some really long trips, I’ve struggled. I get up around 230 on trips, and then struggle to get below 226-227. This was my year, and the upward trend started with the UK and then AUS trips.

    2024-12_0148

    Slowly doing better as I’ve been home since Nov 22. I hope to close out the year at 225 or lower.

    I should track BP, but I don’t. The closest I get it stress, which for me is from my watch. The scale is 1-100, and I show an average for the year of 23. My lowest reading was 17, and the highest was 30. I remember it being above 25 and I know why.

    In general, I am fairly low stress most of the time, and when I feel stressed, I can see it in the readings.

    Exercise

    I try to log all workouts on my watch. If I miss one, or it’s not charged, I try to add a manual one. I don’t always log walks, especially days when I’m just walking a lot without dedicated exercise time. Like in a convention center.

    In any case, here are the workout stats.

    • Indoor Cycling    102
    • Yoga    56
    • Strength Training    54
    • Elliptical    15
    • Pool Swim    8
    • Walking    6
    • Resort Snowboarding    3
    • Indoor Rowing    1
    • Other    1

    That’s a pretty good count overall. I had 246 workouts. Since I often cycle and lift, those can be the same day, but I do a lot of cycling on the road as a quick workout.

    The disappointing bits. Being gone a lot this summer only had me with 8 swims, which was sad. Only 1 of those was over a mile Sad smile

    I also only had 3 days snowboarding, which was also sad, but that was a busy life.

    Still, I think I worked out about 160 days this year by my best guess. We’re still a few weeks short, but that’s about 40-some% of the days that I specifically dedicate to workouts. Less a variety of things, as last year I had 10 types of workouts. Also less yoga, which is something I need to get better at on the road.

  • Big Data or Small Data

    I went to San Francisco for Small Data SF, a conference sponsored by Mother Duck. The premise of the event was that smaller sets of data are both very useful and prevalent. The manifesto speaks to me, as I am a big fan of smaller sets of data for sure. I also think that most of the time we can use less data than we think we need, especially when it’s recent data. That often is more relevant and we end up with contorted queries that try to weight new or old data differently to reflect this. Maybe the best line for me is this one:

    Bigger data has an opportunity cost: Time.

    I think time is a very valuable commodity and large sets of data can slow you down. There’s also the chance that looking at too much data starts to blur the lines of understanding. We may start to miss information in our dataset, or we may find people arguing about different things the data means, because we have so much data that we can find support for any position somewhere in the vast sea of numbers, strings, and dates.

    Big data also has a real cost in resources, often money. One of the examples was from the organizer, who once gave a demo on stage, querying a PB of data.  That’s impressive, and lots of us would want to be able to query our very-large-but-less-than-PB-sized data in minutes. However, the thing that wasn’t disclosed in the demo was the query cost over USD$5k.

    I’ve heard from a number of customers and speakers that most people don’t have big data. Most of us have 100s-of-GB-sized working sets of data, sometimes with TB-sized archives in the same database that slow everything down. If we could easily extract out the useful data, we could query those hundreds of GB more efficiently.

    This is especially true in the era of small devices that can handle something close to a TB of data in a small form factor. With some of the columnar systems that compress data, a TB of raw data might be substantially compressed in Parquet files or an analysis system like DuckDB. In that case, we might realistically search and analyze 1TB of data on a laptop.

    I know that big data is relative, but many of us face challenges with data sizes and query performance. I know lots of you embrace the challenge and see working with TB (or larger) systems as a badge of honor. I also know the reality is that most of us struggle to separate our archive data from current working data in our systems. However, if we could, would most of you want to work with smaller data sets or do you enjoy large ones? I know which way I lean.

    Steve Jones

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