InoteveraGaidhi rinotevera
Amazon SageMaker yeML Workflows
Tekinoroji
Nhungamiro yehunyanzvi
Apache Airflow yeML Workflows
Apache Airflow ipuratifomu yakavhurika-sosi yekunyora, kuronga, uye yekutarisa mafambiro ebasa sekodhi.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
Pa peji ino2 min verenga
Pfupiso
Mukudzidza kwemichina inoita seye conductor inokonzeresa mapaipi edata, kudzidzisazve mabasa, uye fungidziro yebatch pane yakavimbika hurongwa.
Kudzika Kwakadzika
Airflow yakagadzirwa paAirbnb muna 2014 uye yave chirongwa cheApache. Yayo yepakati yekubvisa ndeyeDAG: Yakatungamirwa Acyclic Girafu yemabasa anotsanangurwa muPython, uko mipendero inoisa kurongeka kwekuuraya uye kutsamira. Anoronga anodhirowa aya maDAG, anosarudza kuti ndeapi mabasa akagadzirira, uye oatumira kune vaurayi nevashandi; Webhu UI inoratidza kumhanya nhoroondo, matanda, uye chimiro chebasa. Kune ML, Airflow inoshandiswa zvakanyanya seye orchestrator kwete injini yekombuta: haidzidzise modhi pachayo asi inokonzeresa nhanho sekubvisa data, kuisimbisa, kukanda basa rekudzidzisa paSpark kana Kubernetes pod, uye kutumira mhedzisiro. Vashandi uye masensa vanorega mabasa achidaidza ekunze masisitimu, kumirira mafaera, kana kumhanyisa midziyo. Simba rayo rinovimbika kuronga, kuedzazve, kudzosera kumashure, uye kuoneka kwakajeka mumapaipi akaoma, nguva-yakavakirwa.
Kuitwa muNyika yeChokwadi
Kambani yenhau inomhanyisa zuva nezuva Airflow DAG iyo inodhonza-mushandisi-yekuita matanda, kudzidzisazve modhi yekurudziro, uye inozorodza cache inoshumira.
Chikwata che e-commerce chinoshandisa masensa kumirira faira remutengesi kuti rimhare muchengetedzo yegore risati ratanga basa rekufanotaura.
Kambani yefintech inoronga mabasa eawa yega yega batch-zvibodzwa uko Airflow inokonzeresa modhi ine midziyo mureza wekutengesa kuri kufungidzira.
Chikwata chedata chinoshandisa maAirflow backfills kugadzirisazve mwedzi yenhoroondo data kuburikidza neipi itsva-engineering pombi mushure mekuchinja kwepfungwa.
Ramangwana reApache Airflow yeML Workflows
Airflow 2.x uye 3.x inosimbisa inokurumidza kuronga, iyo TaskFlow API yekuchenesa Python mapaipi, uye data-inoziva kuronga uko maDAG anokonzeresa padataset zvigadziriso kwete wachi dzakatarwa. Kune ML, tarisira kubatana kwakasimba nezvitoro zvemaficha uye kudzidziswa kunofambiswa nechiitiko. Kuyerera kwemhepo kunowedzera kuzvimisikidza seye orchestration layer inoronga maturusi akasarudzika senge dbt, Spark, uye Kubeflow, pane kukwikwidzana navo, ichisimbisa basa rayo senheyo yekuronga yemazuva ano data uye ML stacks.
Kuzvishandisa
Nei zvichikosha
- Mutengo uye bhajeti. Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore.
- Sarudzo dzakajeka. Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete.
- Kudzora kwemhando yepamusoro. Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira.
Chenjera
- Kugadzirisa imwe bhenji kunogona kuvanza yakafara system kushaya simba.
- Infrastructure uye mari yekugadzirisa inowanzotarisirwa pasi.
- Chengetedzo uye kucherechedzwa mapundu anogona kukura sezvo masisitimu anowedzera kuoma.
Matanho anotevera
- Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa.
- Benchmark pasi pechokwadi mutoro uye data mamiriro.
- Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro.
- Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera.
Ramba Uchiongorora
Tsamba yemahara
Tora iyo yemazuva ese AI pfupiso
Nhatu dzakasimbiswa dzeAI nyaya mangwanani ega ega pakati pevhiki, dzakanyorwa neChirungu chakajeka. Yemahara zvachose, hapana ads.
Imwe email zuva rega rega revhiki. Bvisa kunyoresa kamwe chete. Hatimbotengese kana kugovera kero yako.
Zviedze iwe pachako
Take the Apache Airflow for ML Workflows quiz
Mhinduro yepakarepo pamhinduro yega yega, uye chitupa chinogovaniswa chine ID inobatika kana wapedza kosi.
Tsigira dzidzo yemahara yeAI. AI Understanding ndeye 501(c)(3) isingabatsiri - hapana ads, hapana paywall, zvachose. Ita chipo
Mibvunzo inowanzo bvunzwa
Chii chinonzi Apache Airflow yeML Workflows?
Apache Airflow ipuratifomu yakavhurika-sosi yekunyora, kuronga, uye yekutarisa mafambiro ebasa sekodhi. Mukudzidza kwemichina inoita senge conductor inokonzeresa mapaipi edata, kudzidzisazve mabasa, uye fungidziro yebatch pane yakavimbika hurongwa.
MuApache Airflow, chii chinonzi musimboti abstraction chinoshandiswa kutsanangura mafambiro ebasa?
Airflow workflows inotsanangurwa seDAGs muPython, uko mabasa ari node uye mipendero inotsanangura kurongeka kwekuuraya.
Ndeipi basa rinowanzoitwa neAirflow mupombi yeML?
Kuyerera kwemhepo ndeye orchestrator: inokonzeresa uye inoronga nhanho senge kudhirowa data uye mabasa ekudzidzisa pane kuita inorema komputa pachayo.
Ndeipi Airflow inovaka inoshandiswa kumirira mamiriro ekunze, senge faira rinosvika mudura?
Masensor akakosha anoshanda anombomira kufambiswa kwebasa kudzamara mamiriro asangana, senge faira kumhara kana kupatsanurwa kuoneka.
Chii chinonzi Airflow 'backfill' chinokutendera kuti uite?
Kudzosera kumashure kunoita DAG mukati menguva dzakapfuura, inobatsira pakudzokorora nhoroondo mushure mekuchinja kwepombi.
Which Airflow component determines when eligible task instances should be scheduled?
The scheduler evaluates schedules and task eligibility. Upstream success is the default dependency condition, while configured trigger rules can change it.
Ramba uchidzidza
Mazano anoenderana
Mamwe madhairekitori akasarudzirwa nyaya iyi